{
  "data": {
    "a": {
      "slug": "glm-5-3",
      "name": "GLM-5.3",
      "vendor": "Z.ai (Zhipu AI)",
      "vendorUrl": "https://z.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "GLM-5.3 is Z.ai's open-weight mixture-of-experts model for coding and long-horizon agent work, 744B parameters with 40B active and a 1M-token context, published on Hugging Face in FP8 and BF16 under its own licence.",
      "url": "https://www.anchorterminal.com/tools/glm-5-3",
      "markdownUrl": "https://www.anchorterminal.com/tools/glm-5-3.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/glm-5-3.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/glm-5-3.json",
      "dns": "glm-5-3.grade.anchorterminal.com",
      "repo": "https://huggingface.co/zai-org/GLM-5.3",
      "license": "GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "zai-org/GLM-5.3"
        },
        {
          "registry": "huggingface",
          "name": "zai-org/GLM-5.3-BF16"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the GLM-5.3 License. A licensee running a model-as-a-service business with more than US$10 billion of revenue in 12 months must pass Z.AI's security review before commercial use. Running it yourself costs the hardware, 755.7 GB of FP8 files (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-02"
      },
      "docsUrl": "https://huggingface.co/zai-org/GLM-5.3",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "coding",
        "long-context",
        "custom-licence",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.6,
        "grade": "B",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 16,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "capability": 80,
          "interface": 70,
          "reach": 55,
          "risk": 50,
          "upkeep": 58
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-02"
        },
        "negative": 0,
        "verdict": "A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.",
        "bestFor": "Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider",
        "strengths": [
          "Model code in released llama.cpp b11768, vLLM 0.28.0, SGLang 0.5.22 and Transformers 5.12.0",
          "1,048,576 tokens of native context and three reasoning budgets per request",
          "Template renders several tool calls per turn, parsed by glm47 in vLLM and SGLang",
          "Safetensors only, no remote code, files in Z.ai's own organisation with a SHA-256 per shard",
          "Downloadable with no account, and hosted by Z.ai and eight live providers on Hugging Face"
        ],
        "weaknesses": [
          "Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build",
          "No safety evaluation, agent-use guidance or security contact",
          "Thinking is always on, and reasoning_effort only lowers it",
          "Commercial use by model-as-a-service operators above US$10 billion revenue needs Z.AI's security review",
          "The card leaves out limitations, architecture, parameters and cut-off, and zai-org answered 2 of 16 discussions, none since 8 September"
        ],
        "agentNotes": [
          "Start it with `vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3` (vLLM 0.28.0 or later, 8xH200 or 8xH20 per vLLM's recipe)",
          "Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; SGLang's cookbook says glm45 leaves the calls as plain text",
          "Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max",
          "Pass `clear_thinking: true` in chat use, since the template keeps earlier reasoning by default",
          "Don't send `enable_thinking: false`; the template ignores it and always opens a think block",
          "Validate JSON output yourself, since structured output is documented only for Z.ai's hosted API",
          "No Z.ai build fits a 128 GB machine; the full 1M context needs 8xB200 per vLLM's recipe"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.6
          }
        ],
        "editorialScores": {
          "capability": 80,
          "interface": 70,
          "reach": 55,
          "risk": 50,
          "upkeep": 58
        },
        "provenanceScore": 73,
        "checked": {
          "categories": {
            "capability": "2026-11-02",
            "interface": "2026-11-02",
            "reach": "2026-11-02",
            "risk": "2026-11-02",
            "upkeep": "2026-11-02"
          },
          "last": "2026-11-02",
          "oldest": "2026-11-02",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# vLLM's recipe, FP8 on one 8xH200 node\nuv pip install \"vllm\u003e=0.28.0\" --torch-backend=auto\nvllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 \\\n  --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 \\\n  --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice \\\n  --served-model-name glm-5.3\n# or, with llama.cpp and Unsloth's GGUF, a third party's conversion:\nllama-server -hf unsloth/GLM-5.3-GGUF:UD-Q4_K_XL --jinja",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"glm-5.3\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"chat_template_kwargs\": {\"reasoning_effort\": \"low\", \"clear_thinking\": true}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/glm-5-3"
      },
      "sameCompany": [
        "glm-4-5-air",
        "glm-4-7-flash",
        "glm-5-3-flash"
      ],
      "weights": {
        "trainedBy": "Z.ai",
        "builtOn": "GLM-5.2's base model (same base, new post-training)",
        "params": "744B",
        "active": "40B",
        "context": 1048576,
        "goodFor": "Large model for coding and long-horizon agent work with tool calling and always-on reasoning, text only.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "GLM-5.3",
            "url": "https://huggingface.co/zai-org/GLM-5.3",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 755.6,
            "memoryGB": 1024,
            "format": "safetensors"
          },
          {
            "name": "unsloth GLM-5.3-GGUF (UD-Q4_K_XL)",
            "url": "https://huggingface.co/unsloth/GLM-5.3-GGUF",
            "who": "unsloth",
            "precision": "q4_k_xl",
            "sizeGB": 467.29,
            "memoryGB": 1024,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Z.ai's. 467.29 GB of UD-Q4_K_XL weights, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it"
          },
          {
            "name": "GLM-5.3-BF16",
            "url": "https://huggingface.co/zai-org/GLM-5.3-BF16",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 1506.7,
            "memoryGB": 2048,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          }
        ],
        "run": "vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3",
        "runBuild": "GLM-5.3",
        "checked": "2026-10-21",
        "minMemoryGB": 1024
      },
      "family": {
        "lab": "Z.ai (Zhipu AI)",
        "family": "GLM-5",
        "url": "https://www.anchorterminal.com/open-weights/#zai",
        "others": [
          {
            "name": "GLM-5",
            "url": "https://huggingface.co/zai-org/GLM-5",
            "params": "744B-A40B"
          },
          {
            "name": "GLM-5.1",
            "url": "https://huggingface.co/zai-org/GLM-5.1",
            "params": "744B-A40B"
          },
          {
            "name": "GLM-5.2",
            "url": "https://huggingface.co/zai-org/GLM-5.2",
            "params": "744B-A40B"
          },
          {
            "name": "GLM-5.3-Flash",
            "url": "https://huggingface.co/zai-org/GLM-5.3-Flash",
            "params": "320B-A18B",
            "listing": "https://www.anchorterminal.com/tools/glm-5-3-flash"
          }
        ],
        "olderCount": 19,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "JINGSHENG HENGXING TECHNOLOGY PTE.LTD (operator of Z.ai per its terms of use, and registrant of z.ai). The licence names Z.AI",
        "domain": "z.ai",
        "domainRegistered": "2017-12-15",
        "domainNote": "z.ai was registered in 2017 and transferred in October 2024, so its age says little about the company's.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/zai-org/GLM-5.3/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "Z.ai's terms of use name JINGSHENG HENGXING TECHNOLOGY PTE.LTD as the operator of Z.ai, and RDAP names the same company as the registrant of z.ai. The weights' LICENSE names Z.AI as the copyright holder.",
          "Nothing is hosted for this listing, so the GLM-5.3 License stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 11 commits from 27 August to 14 October 2026, whose messages say what changed (two chat template fixes, on 4 September and 14 October, and evaluation results).",
          "z.ai/.well-known/security.txt and docs.z.ai/.well-known/security.txt answered 404 on 21 October 2026."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/glm-5-3.json",
      "live": {
        "slug": "glm-5-3",
        "securityTxt": {
          "url": "https://z.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-10T16:09:36.154640571Z"
        },
        "domain": {
          "domain": "z.ai",
          "registered": "2017-12-15",
          "source": "https://rdap.identitydigital.services/rdap/domain/z.ai",
          "checkedAt": "2026-11-08T15:05:18.801433245Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/zai-org/GLM-5.3/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-10T16:24:04.914285738Z",
            "changedAt": "2026-11-10T16:24:04.914285738Z",
            "fingerprint": "ff4e45ec78e4"
          }
        ],
        "updatedAt": "2026-11-10T16:24:04.914285738Z"
      }
    },
    "answer": "GLM-5.3 scores 64.6 (B) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach.",
    "b": {
      "slug": "ling-3-1-flash-1019",
      "name": "Ling-3.1-flash-1019",
      "vendor": "inclusionAI (Ant Group)",
      "vendorUrl": "https://www.inclusion-ai.org",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Ling-3.1-flash-1019 is inclusionAI's open-weight hybrid reasoning mixture of experts with 560B parameters and 25B active, a post-trained update of Ling-3.1-flash, with switchable thinking, tool calling and a 262,144-token native context, published in FP8 under MIT.",
      "url": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019",
      "markdownUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json",
      "dns": "ling-3-1-flash-1019.grade.anchorterminal.com",
      "repo": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "inclusionAI/Ling-3.1-flash-1019"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under MIT (named in the card's metadata; the repository holds no LICENSE file). Running it yourself costs the hardware, 573.8 GB of FP8 files, which the card serves on 8 H200 or 4 GB300 GPUs (checked 2026-11-10).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "hybrid-attention",
        "reasoning",
        "tool-calling",
        "long-context",
        "mit",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-11-04",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 54.8,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 94,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 60,
          "reach": 60,
          "risk": 45,
          "upkeep": 56
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.",
        "bestFor": "Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding",
        "strengths": [
          "Plain MIT, ungated, with a hash for every shard",
          "Released vLLM, SGLang, Transformers and llama.cpp all have the architecture",
          "A 262,144-token native context, and 1M with YaRN per SGLang's cookbook",
          "A training-content summary that names source categories, the size band and a collection date",
          "Updated a week before this check"
        ],
        "weaknesses": [
          "574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it",
          "The card says 1M tokens of context where the files give 262,144",
          "The tool-call format is only in the template",
          "No safety results, no agent guidance and no security contact",
          "No inference provider mapped for this release, only for the earlier one",
          "Neither question on the repository has a reply"
        ],
        "agentNotes": [
          "Serve it with SGLang 0.5.23 or later on 8 H200 or 4 GB300 GPUs, per the card, and use this repository's name as the model path, not the earlier one the card's command shows",
          "With vLLM pass `--trust-remote-code`, `--tool-call-parser ling3` and `--reasoning-parser ling3`",
          "Set `chat_template_kwargs` `enable_thinking` false for direct answers. Reasoning comes back in `reasoning_content` per SGLang's cookbook",
          "Plan on 262,144 tokens of context. The 1M figure needs the YaRN override in SGLang's cookbook",
          "Use temperature 1.0, top_p 0.95 and top_k 20, per the card",
          "Validate JSON output yourself, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 54.8
          }
        ],
        "editorialScores": {
          "interface": 60,
          "reach": 60,
          "risk": 45,
          "upkeep": 56
        },
        "provenanceScore": 61,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# with SGLang 0.5.23 or later, on 8 H200 GPUs:\npython3 -m sglang.launch_server --model-path inclusionAI/Ling-3.1-flash-1019 \\\n  --tp 8 --ep 8 --speculative-algorithm NEXTN --host 0.0.0.0 --port 30000\n# or with vLLM 0.33.0, per the card's serve command:\nvllm serve inclusionAI/Ling-3.1-flash-1019 --trust-remote-code --tensor-parallel-size 8 \\\n  --enable-prefix-caching --enable-expert-parallel --mamba-cache-mode align \\\n  --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3\n# or, with llama.cpp and bartowski's GGUF, a third party's conversion:\nllama-server -hf bartowski/Ling-3.1-flash-1019-GGUF:Q4_K_M --jinja",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"inclusionAI/Ling-3.1-flash-1019\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"enable_thinking\": false}}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/ling-3-1-flash-1019"
      },
      "sameCompany": [
        "ming-3-0-asr-tiny",
        "ming-3-0-audio-flash",
        "ming-3-0-audio-tiny",
        "ming-3-0-tts-tiny",
        "lbs-27b",
        "ling-3-0-tiny"
      ],
      "weights": {
        "trainedBy": "inclusionAI (Ant Group)",
        "builtOn": "inclusionAI/Ling-3.1-flash, post-trained further (named on the card; the metadata names no base model)",
        "params": "560B (25B active)",
        "context": 262144,
        "goodFor": "Large hybrid reasoning model for agents, office work and software engineering on a multi-GPU server, with thinking switchable per request. It needs about 690 GB of GPU memory in FP8.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "bartowski Ling-3.1-flash-1019-GGUF (Q4_K_M)",
            "url": "https://huggingface.co/bartowski/Ling-3.1-flash-1019-GGUF",
            "who": "bartowski",
            "precision": "q4_k_m",
            "sizeGB": 357.97,
            "memoryGB": 512,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From bartowski, a third party's conversion and not inclusionAI's. 357.97 GB of Q4_K_M weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "Ling-3.1-flash-1019",
            "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 573.78,
            "memoryGB": 1024,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ],
            "note": "The release itself, FP8 E4M3 weights in 128×128 blocks. inclusionAI publishes no smaller build"
          }
        ],
        "run": "python3 -m sglang.launch_server --model-path inclusionAI/Ling-3.1-flash-1019 --tp 8 --ep 8 --speculative-algorithm NEXTN",
        "runBuild": "Ling-3.1-flash-1019",
        "checked": "2026-11-10",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "inclusionAI (Ant Group)",
        "family": "Ling 3",
        "url": "https://www.anchorterminal.com/open-weights/#inclusionai",
        "others": [
          {
            "name": "Ling-3.0-flash",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash",
            "params": "124B total, 5.1B active"
          },
          {
            "name": "Ling-3.0-flash-base",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base",
            "params": "124B total, 5.1B active"
          },
          {
            "name": "Ling-3.0-flash-base-30T",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-30T",
            "params": "124B total, 5.1B active"
          },
          {
            "name": "Ling-3.0-flash-base-midtrain",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-midtrain",
            "params": "124B total, 5.1B active"
          },
          {
            "name": "Ling-3.0-flash-Fin",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin",
            "params": "124B total, 5.1B active"
          },
          {
            "name": "Ling-3.0-flash-VL",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-VL",
            "params": "124B total, 5.5B active"
          },
          {
            "name": "Ling-3.0-flash-dspark",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-dspark",
            "params": "1.36B (draft)"
          },
          {
            "name": "Ling-3.0-flash-singprobe",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-singprobe",
            "params": "5.18M (probe)"
          },
          {
            "name": "Ling-3.0-tiny",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny",
            "params": "7.9B total, 1.3B active",
            "listing": "https://www.anchorterminal.com/tools/ling-3-0-tiny"
          },
          {
            "name": "Ling-3.0-tiny-base",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base",
            "params": "7.9B total, 1.3B active"
          },
          {
            "name": "Ling-3.0-tiny-base-30T",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-30T",
            "params": "7.9B total, 1.3B active"
          },
          {
            "name": "Ling-3.0-tiny-base-midtrain",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-midtrain",
            "params": "7.9B total, 1.3B active"
          },
          {
            "name": "Ling-3.0-tiny-singprobe",
            "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-singprobe",
            "params": "3.22M (probe)"
          },
          {
            "name": "Ling-3.1-flash",
            "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash",
            "params": "560B total, 25B active"
          },
          {
            "name": "Ling-3.1-flash-base",
            "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash-base",
            "params": "560B total, 25B active"
          }
        ],
        "olderCount": 54
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Ant Intelligence (Hang Zhou) Technology Co., Ltd (named as provider in the training-content summary); inclusionAI, Ant Group in the site footer of inclusion-ai.org",
        "domain": "inclusion-ai.org",
        "domainRegistered": "2025-04-03",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI. The domain registration date is carried from the RDAP check made for the Ming 3.0 listings on 21 October 2026.",
          "Nothing is hosted by the publisher, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the Hugging Face commit history, 8 commits from 27 October to 4 November 2026, the last three card edits.",
          "www.inclusion-ai.org/.well-known/security.txt answered 404 on 10 November 2026."
        ],
        "score": 61
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.json"
    },
    "edges": [
      {
        "by": 10,
        "category": "interface",
        "leads": "glm-5-3",
        "name": "Agent interface",
        "reasons": {
          "a": "A Jinja chat template sits in the repository, for 20. The tool-calling format is 10, since it is defined only by the template and the glm47 parser is named by vLLM and SGLang rather than by Z.ai. The template takes several calls in one turn, for 20. Structured output is 0, with nothing on the card and JSON documented only for the hosted API. Reasoning control is 10, a per-request budget through reasoning_effort with the reasoning in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rope scaling.",
          "b": "Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning. Tool-calling format 10, only the template says how tools are declared (JSON in \u003ctools\u003e) and how calls come back (\u003ctool_call\u003ename with \u003carg_key\u003e and \u003carg_value\u003e pairs). Trained tool calling 20, the template tells the model it may call one or more functions and loops over every entry in an assistant message's tool_calls, and the card reports gains on agentic benchmarks, AA-Briefcase and AutomationBench-AA among them. Structured output 0, the card doesn't document JSON or JSON Schema output. Reasoning control 0, the card documents turning thinking on or off per request with chat_template_kwargs enable_thinking, and names the ling3 reasoning parser, but doesn't say where the reasoning text comes back. Context 10, 262,144 tokens natively in config.json (max_position_embeddings 262144, rope_scaling null) and per SGLang's cookbook. 20 + 10 + 20 + 0 + 0 + 10 = 60."
        },
        "scores": {
          "a": 70,
          "b": 60
        }
      },
      {
        "by": 5,
        "category": "reach",
        "leads": "ling-3-1-flash-1019",
        "name": "Reach",
        "reasons": {
          "a": "Memory earns nothing, since Z.ai's smallest build is the 755.6 GB FP8 one, about 907 GB with the fifth added, and Ollama only lists a cloud entry. Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio have no local build. Z.ai publishes one quantised build, FP8, for 10, since the BF16 repository is the full precision. The GLM-5.3 License is a custom licence that is free for commercial use below a revenue threshold, for 10. The files download with no account or gate, for 10, and Z.ai's own API plus eight live providers on Hugging Face serve it, for 5.",
          "b": "Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build. Runtimes 25, Released model code in Transformers 5.22.2 (bailing_hybrid), vLLM 0.33.0 (BailingMoeV3ForCausalLM, with ling3 tool and reasoning parsers), SGLang 0.5.23 (bailing_moe_v3.py, its bailing_hybrid config and MTP module) and llama.cpp b12242 (bailingmoe3), and Ollama, credited through its pinned llama.cpp as on the Ling-3.0-tiny listing: v0.40.16 sets LLAMA_CPP_VERSION to b12177. Builds 10, the release is FP8, the one quantised precision inclusionAI publishes for it. Terms 15, MIT in the card's metadata, with no use policy or other terms added on the card or in the repository. Download 10, the Hub API's model info gives gated false on 10 November 2026, so the files download with no account and no terms to accept. Hosted 0, the Hub API's provider mapping is empty for this repository on 10 November 2026. 0 + 25 + 10 + 15 + 10 + 0 = 60."
        },
        "scores": {
          "a": 55,
          "b": 60
        }
      },
      {
        "by": 5,
        "category": "risk",
        "leads": "glm-5-3",
        "name": "Risk",
        "reasons": {
          "a": "File safety is full, with safetensors only, no Python in the repository and no remote code needed in Transformers 5.12.0 or later. Provenance is full, files in the zai-org organisation Z.ai links to with a SHA-256 for every shard. Safety evaluation is 0, because the blog mentions safety evaluation and hardening but publishes no results, and agent guidance is 0, with nothing on refusals, prompt injection or cautions. Licence risk is 10, losing 5 for the security review that model-as-a-service operators above US$10 billion of revenue must pass. The security programme is 0, with no security.txt, no SECURITY.md and no advisories.",
          "b": "File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the repository's configuration_bailing_moe_v3.py, since vLLM 0.33.0 registers no bailing_hybrid config of its own. Provenance 15, files in the inclusionAI organisation that inclusion-ai.org links to, per the Ling-3.0-tiny listing (10). Safety evaluation 0, no safety results for the model on its card or in the training-content summary. Agent guidance 0, the card has nothing on prompt injection, refusals or safeguards, and inclusionAI publishes no guardrail probe for this model as it did for Ling 3.0. Licence risk 15, MIT with no use policy, no field-of-use limits, no threshold and no clause letting inclusionAI change or revoke it. Security programme 0, www.inclusion-ai.org answers 404 for security.txt on 10 November 2026, and the Ling-3.0-tiny listing found no SECURITY.md or disclosure policy in the inclusionAI .github repository. 15 + 15 + 0 + 0 + 15 + 0 = 45."
        },
        "scores": {
          "a": 50,
          "b": 45
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Z.ai (Zhipu AI)",
        "b": "inclusionAI (Ant Group)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators)",
        "b": "MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-15",
        "b": "2026-11-04",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "2.8/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "GLM-5.3 scores 64.6 (B) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach.",
        "question": "Which is better for AI agents, GLM-5.3 or Ling-3.1-flash-1019?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 50 against 45",
          "Agent interface, 70 against 60"
        ],
        "also": null,
        "goodFor": "Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider",
        "slug": "glm-5-3",
        "watchFor": "Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build"
      },
      {
        "aheadOn": [
          "Reach, 60 against 55"
        ],
        "also": null,
        "goodFor": "Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding",
        "slug": "ling-3-1-flash-1019",
        "watchFor": "574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it"
      }
    ],
    "history": null,
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3.json",
        "title": "Agents-A1-4B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-1-flash-1019.json",
        "title": "Agents-A1-4B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3.json",
        "title": "Apertus v1.5 8B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019.json",
        "title": "Apertus v1.5 8B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3.json",
        "title": "Apodex-1.1-mini vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-1-flash-1019.json",
        "title": "Apodex-1.1-mini vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3.json",
        "title": "Arete-27B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-1-flash-1019.json",
        "title": "Arete-27B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.json",
        "title": "BigBang-v1 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-1-flash-1019.json",
        "title": "BigBang-v1 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3.json",
        "title": "Carbon-X vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-1-flash-1019.json",
        "title": "Carbon-X vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-glm-5-3.json",
        "title": "Cola2 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019.json",
        "title": "Cola2 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.json",
        "title": "Cosmos-Reason2-2B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-1-flash-1019.json",
        "title": "Cosmos-Reason2-2B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3.json",
        "title": "Darwin-36B-Opus vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.json",
        "title": "Darwin-36B-Opus vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.json",
        "title": "DeepSeek-V3.2 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-1-flash-1019.json",
        "title": "DeepSeek-V3.2 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3.json",
        "title": "DeepSeek V4.1 Flash vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ling-3-1-flash-1019.json",
        "title": "DeepSeek V4.1 Flash vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3.json",
        "title": "DeepSeek-V4-Flash-0731 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ling-3-1-flash-1019.json",
        "title": "DeepSeek-V4-Flash-0731 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-glm-5-3.json",
        "title": "Devstral Small 2 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-ling-3-1-flash-1019.json",
        "title": "Devstral Small 2 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3.json",
        "title": "DiffusionGemma 26B A4B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ling-3-1-flash-1019.json",
        "title": "DiffusionGemma 26B A4B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3.json",
        "title": "EXAONE 4.5 33B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019.json",
        "title": "EXAONE 4.5 33B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3.json",
        "title": "Gemma 4 12B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ling-3-1-flash-1019.json",
        "title": "Gemma 4 12B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3.json",
        "title": "Gemma 4 26B A4B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ling-3-1-flash-1019.json",
        "title": "Gemma 4 26B A4B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3.json",
        "title": "Gemma 4 31B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ling-3-1-flash-1019.json",
        "title": "Gemma 4 31B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3.json",
        "title": "Gemma 4 E2B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ling-3-1-flash-1019.json",
        "title": "Gemma 4 E2B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3.json",
        "title": "Gemma 4 E4B IT vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ling-3-1-flash-1019.json",
        "title": "Gemma 4 E4B IT vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3.json",
        "title": "GLM-4.5-Air vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-ling-3-1-flash-1019.json",
        "title": "GLM-4.5-Air vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3.json",
        "title": "GLM-4.7-Flash vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ling-3-1-flash-1019.json",
        "title": "GLM-4.7-Flash vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019.json",
        "title": "GLM-5.3-Flash vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.json",
        "title": "GLM-5.3 vs GLM-5.3-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.json",
        "title": "GLM-5.3 vs gpt-oss-120b",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b.json",
        "title": "GLM-5.3 vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-30b.json",
        "title": "GLM-5.3 vs Granite 4.2 30B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b.json",
        "title": "GLM-5.3 vs Granite 4.2 3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-8b.json",
        "title": "GLM-5.3 vs Granite 4.2 8B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy-memory-30b-a3b.json",
        "title": "GLM-5.3 vs Hy-Memory-30B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy-memory-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3.json",
        "title": "GLM-5.3 vs Hy3",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.json",
        "title": "GLM-5.3 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.json",
        "title": "GLM-5.3 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "GLM-5.3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3.json",
        "title": "GLM-5.3 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3-1-pro.json",
        "title": "GLM-5.3 vs Kimi K3.1 Pro",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3-1-pro"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1.json",
        "title": "GLM-5.3 vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kronos.json",
        "title": "GLM-5.3 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.json",
        "title": "GLM-5.3 vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.json",
        "title": "GLM-5.3 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1.json",
        "title": "GLM-5.3 vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b.json",
        "title": "GLM-5.3 vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b.json",
        "title": "GLM-5.3 vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b.json",
        "title": "GLM-5.3 vs LFM3-1.7B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-audio-2b.json",
        "title": "GLM-5.3 vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-omni-2b.json",
        "title": "GLM-5.3 vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-omni-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-vl-2b.json",
        "title": "GLM-5.3 vs LFM3-VL-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny.json",
        "title": "GLM-5.3 vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-longcat-2-5.json",
        "title": "GLM-5.3 vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "GLM-5.3 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-flash-rl.json",
        "title": "GLM-5.3 vs MiMo-V2.6-Flash-RL",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-flash-rl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.json",
        "title": "GLM-5.3 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-1b.json",
        "title": "GLM-5.3 vs MiniCPM-V 4.7 1B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-1b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "GLM-5.3 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.json",
        "title": "GLM-5.3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.json",
        "title": "GLM-5.3 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7.json",
        "title": "GLM-5.3 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m3-1-flash.json",
        "title": "GLM-5.3 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m3-1-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-mistral-large-4.json",
        "title": "GLM-5.3 vs Mistral Large 4",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-mistral-large-4"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b.json",
        "title": "GLM-5.3 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-2-3b.json",
        "title": "GLM-5.3 vs Nanbeige4.2-3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-2-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-3-33b.json",
        "title": "GLM-5.3 vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-3-33b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-bolt-e4b-4gb.json",
        "title": "GLM-5.3 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-bolt-e4b-4gb"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "GLM-5.3 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b.json",
        "title": "GLM-5.3 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b.json",
        "title": "GLM-5.3 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "GLM-5.3 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.json",
        "title": "GLM-5.3 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "GLM-5.3 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0.json",
        "title": "GLM-5.3 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.json",
        "title": "GLM-5.3 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think.json",
        "title": "GLM-5.3 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b.json",
        "title": "GLM-5.3 vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b.json",
        "title": "GLM-5.3 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b.json",
        "title": "GLM-5.3 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b.json",
        "title": "GLM-5.3 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-otel-2-0-llm-31b-it.json",
        "title": "GLM-5.3 vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen-agentworld-35b-a3b.json",
        "title": "GLM-5.3 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "GLM-5.3 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507.json",
        "title": "GLM-5.3 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b.json",
        "title": "GLM-5.3 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b.json",
        "title": "GLM-5.3 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b.json",
        "title": "GLM-5.3 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b.json",
        "title": "GLM-5.3 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b.json",
        "title": "GLM-5.3 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b.json",
        "title": "GLM-5.3 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b.json",
        "title": "GLM-5.3 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b.json",
        "title": "GLM-5.3 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b.json",
        "title": "GLM-5.3 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next.json",
        "title": "GLM-5.3 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next.json",
        "title": "GLM-5.3 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct.json",
        "title": "GLM-5.3 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2.json",
        "title": "GLM-5.3 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint.json",
        "title": "GLM-5.3 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ripple-65b-preview.json",
        "title": "GLM-5.3 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-sensenova-loop-9b-preview.json",
        "title": "GLM-5.3 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.json",
        "title": "GLM-5.3 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b.json",
        "title": "GLM-5.3 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-step-3-7-flash.json",
        "title": "GLM-5.3 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b.json",
        "title": "GLM-5.3 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "GLM-5.3 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b.json",
        "title": "GLM-5.3 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2.json",
        "title": "GLM-5.3 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-2b.json",
        "title": "GLM-5.3 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-4b.json",
        "title": "GLM-5.3 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-zaya1-8b.json",
        "title": "GLM-5.3 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-1-flash-1019.json",
        "title": "gpt-oss-120b vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ling-3-1-flash-1019.json",
        "title": "gpt-oss-20b vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019.json",
        "title": "Granite 4.2 30B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ling-3-1-flash-1019.json",
        "title": "Granite 4.2 3B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-1-flash-1019.json",
        "title": "Granite 4.2 8B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ling-3-1-flash-1019.json",
        "title": "Hy-Memory-30B-A3B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-ling-3-1-flash-1019.json",
        "title": "Hy3 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-1-flash-1019.json",
        "title": "Inkling-Small vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-1-flash-1019.json",
        "title": "Inkling vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ling-3-1-flash-1019.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ling-3-1-flash-1019.json",
        "title": "Kimi K3.1 Pro vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-1-flash-1019.json",
        "title": "Kimi K3 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-ling-3-1-flash-1019.json",
        "title": "Kolibri-1 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-ling-3-1-flash-1019.json",
        "title": "Kronos vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019.json",
        "title": "Laguna M.1 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-1-flash-1019.json",
        "title": "Laguna S 2.1 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-1-flash-1019.json",
        "title": "Laguna XS 2.1 vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-1-flash-1019.json",
        "title": "LBS-27B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ling-3-1-flash-1019.json",
        "title": "LFM2.5-2.6B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019.json",
        "title": "LFM3-1.7B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ling-3-1-flash-1019.json",
        "title": "LFM3-Audio-2B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ling-3-1-flash-1019.json",
        "title": "LFM3-Omni-2B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ling-3-1-flash-1019.json",
        "title": "LFM3-VL-2B vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ling-3-1-flash-1019.json",
        "title": "Ling-3.0-tiny vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ling-3-1-flash-1019"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-longcat-2-5.json",
        "title": "Ling-3.1-flash-1019 vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Ling-3.1-flash-1019 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-flash-rl.json",
        "title": "Ling-3.1-flash-1019 vs MiMo-V2.6-Flash-RL",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-flash-rl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-o-4-5.json",
        "title": "Ling-3.1-flash-1019 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-1b.json",
        "title": "Ling-3.1-flash-1019 vs MiniCPM-V 4.7 1B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-1b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm5-2b.json",
        "title": "Ling-3.1-flash-1019 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-5.json",
        "title": "Ling-3.1-flash-1019 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-7.json",
        "title": "Ling-3.1-flash-1019 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m3-1-flash.json",
        "title": "Ling-3.1-flash-1019 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m3-1-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mistral-large-4.json",
        "title": "Ling-3.1-flash-1019 vs Mistral Large 4",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mistral-large-4"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-muse-glimmer-30b.json",
        "title": "Ling-3.1-flash-1019 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-2-3b.json",
        "title": "Ling-3.1-flash-1019 vs Nanbeige4.2-3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-2-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-3-33b.json",
        "title": "Ling-3.1-flash-1019 vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-3-33b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-bolt-e4b-4gb.json",
        "title": "Ling-3.1-flash-1019 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-bolt-e4b-4gb"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-super-120b-a12b.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Ling-3.1-flash-1019 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0.json",
        "title": "Ling-3.1-flash-1019 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0.json",
        "title": "Ling-3.1-flash-1019 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-olmo-3-7b-think.json",
        "title": "Ling-3.1-flash-1019 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b.json",
        "title": "Ling-3.1-flash-1019 vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-35b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-397b.json",
        "title": "Ling-3.1-flash-1019 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-9b.json",
        "title": "Ling-3.1-flash-1019 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-otel-2-0-llm-31b-it.json",
        "title": "Ling-3.1-flash-1019 vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen-agentworld-35b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-4b-instruct-2507.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-0-8b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-122b-a10b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-2b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-397b-a17b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-4b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-9b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-27b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-35b-a3b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-27b.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-next.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-2b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-32b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-4b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-8b-instruct.json",
        "title": "Ling-3.1-flash-1019 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Ling-3.1-flash-1019 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-recursive-flint.json",
        "title": "Ling-3.1-flash-1019 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ripple-65b-preview.json",
        "title": "Ling-3.1-flash-1019 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview.json",
        "title": "Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-smollm3-3b.json",
        "title": "Ling-3.1-flash-1019 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-spark-x2-6-4b.json",
        "title": "Ling-3.1-flash-1019 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-step-3-7-flash.json",
        "title": "Ling-3.1-flash-1019 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Ling-3.1-flash-1019 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Ling-3.1-flash-1019 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Ling-3.1-flash-1019 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-unlimited-ocr-2.json",
        "title": "Ling-3.1-flash-1019 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-2b.json",
        "title": "Ling-3.1-flash-1019 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-4b.json",
        "title": "Ling-3.1-flash-1019 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.json",
        "title": "Ling-3.1-flash-1019 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "ling-3-1-flash-1019",
        "glm-5-3": 55,
        "key": "reach",
        "ling-3-1-flash-1019": 60,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 5,
        "edge": "glm-5-3",
        "glm-5-3": 50,
        "key": "risk",
        "ling-3-1-flash-1019": 45,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 10,
        "edge": "glm-5-3",
        "glm-5-3": 70,
        "key": "interface",
        "ling-3-1-flash-1019": 60,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 2,
        "edge": "glm-5-3",
        "glm-5-3": 58,
        "key": "upkeep",
        "ling-3-1-flash-1019": 56,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "GLM-5.3 scores 64.6 (B) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "glm-5-3": "A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.",
      "ling-3-1-flash-1019": "inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019",
    "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019.min.md"
  },
  "markdown": "GLM-5.3 scores 64.6 (B) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach. Both do open-weight models you run yourself.\n\n- GLM-5.3: grade B, 64.6/100, rank #21 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-5-3.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-5-3.json\n- Ling-3.1-flash-1019: grade C, 54.8/100, rank #126 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/ling-3-1-flash-1019.md · JSON https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### GLM-5.3 (B)\n\nGood for: Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider\n\nAhead on:\n- Risk, 50 against 45\n- Agent interface, 70 against 60\n\nWatch for: Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build\n\n### Ling-3.1-flash-1019 (C)\n\nGood for: Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding\n\nAhead on:\n- Reach, 60 against 55\n\nWatch for: 574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it\n\n\n## Why the edge\n\n### Agent interface: GLM-5.3 +10\n\n- GLM-5.3 (70): A Jinja chat template sits in the repository, for 20. The tool-calling format is 10, since it is defined only by the template and the glm47 parser is named by vLLM and SGLang rather than by Z.ai. The template takes several calls in one turn, for 20. Structured output is 0, with nothing on the card and JSON documented only for the hosted API. Reasoning control is 10, a per-request budget through reasoning_effort with the reasoning in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rope scaling.\n- Ling-3.1-flash-1019 (60): Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning. Tool-calling format 10, only the template says how tools are declared (JSON in \u003ctools\u003e) and how calls come back (\u003ctool_call\u003ename with \u003carg_key\u003e and \u003carg_value\u003e pairs). Trained tool calling 20, the template tells the model it may call one or more functions and loops over every entry in an assistant message's tool_calls, and the card reports gains on agentic benchmarks, AA-Briefcase and AutomationBench-AA among them. Structured output 0, the card doesn't document JSON or JSON Schema output. Reasoning control 0, the card documents turning thinking on or off per request with chat_template_kwargs enable_thinking, and names the ling3 reasoning parser, but doesn't say where the reasoning text comes back. Context 10, 262,144 tokens natively in config.json (max_position_embeddings 262144, rope_scaling null) and per SGLang's cookbook. 20 + 10 + 20 + 0 + 0 + 10 = 60.\n\n### Reach: Ling-3.1-flash-1019 +5\n\n- GLM-5.3 (55): Memory earns nothing, since Z.ai's smallest build is the 755.6 GB FP8 one, about 907 GB with the fifth added, and Ollama only lists a cloud entry. Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio have no local build. Z.ai publishes one quantised build, FP8, for 10, since the BF16 repository is the full precision. The GLM-5.3 License is a custom licence that is free for commercial use below a revenue threshold, for 10. The files download with no account or gate, for 10, and Z.ai's own API plus eight live providers on Hugging Face serve it, for 5.\n- Ling-3.1-flash-1019 (60): Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build. Runtimes 25, Released model code in Transformers 5.22.2 (bailing_hybrid), vLLM 0.33.0 (BailingMoeV3ForCausalLM, with ling3 tool and reasoning parsers), SGLang 0.5.23 (bailing_moe_v3.py, its bailing_hybrid config and MTP module) and llama.cpp b12242 (bailingmoe3), and Ollama, credited through its pinned llama.cpp as on the Ling-3.0-tiny listing: v0.40.16 sets LLAMA_CPP_VERSION to b12177. Builds 10, the release is FP8, the one quantised precision inclusionAI publishes for it. Terms 15, MIT in the card's metadata, with no use policy or other terms added on the card or in the repository. Download 10, the Hub API's model info gives gated false on 10 November 2026, so the files download with no account and no terms to accept. Hosted 0, the Hub API's provider mapping is empty for this repository on 10 November 2026. 0 + 25 + 10 + 15 + 10 + 0 = 60.\n\n### Risk: GLM-5.3 +5\n\n- GLM-5.3 (50): File safety is full, with safetensors only, no Python in the repository and no remote code needed in Transformers 5.12.0 or later. Provenance is full, files in the zai-org organisation Z.ai links to with a SHA-256 for every shard. Safety evaluation is 0, because the blog mentions safety evaluation and hardening but publishes no results, and agent guidance is 0, with nothing on refusals, prompt injection or cautions. Licence risk is 10, losing 5 for the security review that model-as-a-service operators above US$10 billion of revenue must pass. The security programme is 0, with no security.txt, no SECURITY.md and no advisories.\n- Ling-3.1-flash-1019 (45): File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the repository's configuration_bailing_moe_v3.py, since vLLM 0.33.0 registers no bailing_hybrid config of its own. Provenance 15, files in the inclusionAI organisation that inclusion-ai.org links to, per the Ling-3.0-tiny listing (10). Safety evaluation 0, no safety results for the model on its card or in the training-content summary. Agent guidance 0, the card has nothing on prompt injection, refusals or safeguards, and inclusionAI publishes no guardrail probe for this model as it did for Ling 3.0. Licence risk 15, MIT with no use policy, no field-of-use limits, no threshold and no clause letting inclusionAI change or revoke it. Security programme 0, www.inclusion-ai.org answers 404 for security.txt on 10 November 2026, and the Ling-3.0-tiny listing found no SECURITY.md or disclosure policy in the inclusionAI .github repository. 15 + 15 + 0 + 0 + 15 + 0 = 45.\n\n## Score by category\n\n| Category | Weight | GLM-5.3 | Ling-3.1-flash-1019 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 60 | Ling-3.1-flash-1019 +5 |\n| Risk | 20% (20 this run) | 50 | 45 | GLM-5.3 +5 |\n| Agent interface | 10% (10 this run) | 70 | 60 | GLM-5.3 +10 |\n| Documentation and upkeep | 10% (10 this run) | 58 | 56 | GLM-5.3 +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.6 · B** | **54.8 · C** | |\n\n## Facts side by side\n\n| Fact | GLM-5.3 | Ling-3.1-flash-1019 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Z.ai (Zhipu AI) | inclusionAI (Ant Group) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators) | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-15 | 2026-11-04 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 2.8/5 (4) | none |\n\n## Verdicts\n\n**GLM-5.3.** A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.\n\n**Ling-3.1-flash-1019.** inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.\n\n## Before you call either\n\n### GLM-5.3\n\n1. Start it with `vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3` (vLLM 0.28.0 or later, 8xH200 or 8xH20 per vLLM's recipe)\n2. Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; SGLang's cookbook says glm45 leaves the calls as plain text\n3. Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max\n4. Pass `clear_thinking: true` in chat use, since the template keeps earlier reasoning by default\n5. Don't send `enable_thinking: false`; the template ignores it and always opens a think block\n6. Validate JSON output yourself, since structured output is documented only for Z.ai's hosted API\n7. No Z.ai build fits a 128 GB machine; the full 1M context needs 8xB200 per vLLM's recipe\n\n### Ling-3.1-flash-1019\n\n1. Serve it with SGLang 0.5.23 or later on 8 H200 or 4 GB300 GPUs, per the card, and use this repository's name as the model path, not the earlier one the card's command shows\n2. With vLLM pass `--trust-remote-code`, `--tool-call-parser ling3` and `--reasoning-parser ling3`\n3. Set `chat_template_kwargs` `enable_thinking` false for direct answers. Reasoning comes back in `reasoning_content` per SGLang's cookbook\n4. Plan on 262,144 tokens of context. The 1M figure needs the YaRN override in SGLang's cookbook\n5. Use temperature 1.0, top_p 0.95 and top_k 20, per the card\n6. Validate JSON output yourself, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, GLM-5.3 or Ling-3.1-flash-1019?\n\nGLM-5.3 scores 64.6 (B) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019.json, and with the fewest tokens: https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"glm-5-3\", \"b\": \"ling-3-1-flash-1019\"}`. From a terminal: `anchor compare glm-5-3 ling-3-1-flash-1019`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/glm-5-3.json and https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json\n\n## Other comparisons with GLM-5.3 or Ling-3.1-flash-1019\n\n- [Agents-A1-4B vs GLM-5.3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3.md)\n- [Agents-A1-4B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-1-flash-1019.md)\n- [Apertus v1.5 8B vs GLM-5.3](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3.md)\n- [Apertus v1.5 8B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019.md)\n- [Apodex-1.1-mini vs GLM-5.3](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3.md)\n- [Apodex-1.1-mini vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-1-flash-1019.md)\n- [Arete-27B vs GLM-5.3](https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3.md)\n- [Arete-27B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-1-flash-1019.md)\n- [BigBang-v1 vs GLM-5.3](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.md)\n- [BigBang-v1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-1-flash-1019.md)\n- [Carbon-X vs GLM-5.3](https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3.md)\n- [Carbon-X vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/carbon-x-vs-ling-3-1-flash-1019.md)\n- [Cola2 vs GLM-5.3](https://www.anchorterminal.com/compare/cola2-vs-glm-5-3.md)\n- [Cola2 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019.md)\n- [Cosmos-Reason2-2B vs GLM-5.3](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.md)\n- [Cosmos-Reason2-2B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-1-flash-1019.md)\n- [Darwin-36B-Opus vs GLM-5.3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3.md)\n- [Darwin-36B-Opus vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.md)\n- [DeepSeek-V3.2 vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.md)\n- [DeepSeek-V3.2 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-1-flash-1019.md)\n- [DeepSeek V4.1 Flash vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3.md)\n- [DeepSeek V4.1 Flash vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ling-3-1-flash-1019.md)\n- [DeepSeek-V4-Flash-0731 vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3.md)\n- [DeepSeek-V4-Flash-0731 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ling-3-1-flash-1019.md)\n- [Devstral Small 2 vs GLM-5.3](https://www.anchorterminal.com/compare/devstral-small-2-vs-glm-5-3.md)\n- [Devstral Small 2 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/devstral-small-2-vs-ling-3-1-flash-1019.md)\n- [DiffusionGemma 26B A4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3.md)\n- [DiffusionGemma 26B A4B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ling-3-1-flash-1019.md)\n- [EXAONE 4.5 33B vs GLM-5.3](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3.md)\n- [EXAONE 4.5 33B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019.md)\n- [Gemma 4 12B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3.md)\n- [Gemma 4 12B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ling-3-1-flash-1019.md)\n- [Gemma 4 26B A4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3.md)\n- [Gemma 4 26B A4B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ling-3-1-flash-1019.md)\n- [Gemma 4 31B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3.md)\n- [Gemma 4 31B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ling-3-1-flash-1019.md)\n- [Gemma 4 E2B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3.md)\n- [Gemma 4 E2B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ling-3-1-flash-1019.md)\n- [Gemma 4 E4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3.md)\n- [Gemma 4 E4B IT vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ling-3-1-flash-1019.md)\n- [GLM-4.5-Air vs GLM-5.3](https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3.md)\n- [GLM-4.5-Air vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/glm-4-5-air-vs-ling-3-1-flash-1019.md)\n- [GLM-4.7-Flash vs GLM-5.3](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3.md)\n- [GLM-4.7-Flash vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ling-3-1-flash-1019.md)\n- [GLM-5.3-Flash vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019.md)\n- [GLM-5.3 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.md)\n- [GLM-5.3 vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.md)\n- [GLM-5.3 vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b.md)\n- [GLM-5.3 vs Granite 4.2 30B](https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-30b.md)\n- [GLM-5.3 vs Granite 4.2 3B](https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b.md)\n- [GLM-5.3 vs Granite 4.2 8B](https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-8b.md)\n- [GLM-5.3 vs Hy-Memory-30B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-hy-memory-30b-a3b.md)\n- [GLM-5.3 vs Hy3](https://www.anchorterminal.com/compare/glm-5-3-vs-hy3.md)\n- [GLM-5.3 vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.md)\n- [GLM-5.3 vs Inkling-Small](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.md)\n- [GLM-5.3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-5.3 vs Kimi K3](https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3.md)\n- [GLM-5.3 vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3-1-pro.md)\n- [GLM-5.3 vs Kolibri-1](https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1.md)\n- [GLM-5.3 vs Kronos](https://www.anchorterminal.com/compare/glm-5-3-vs-kronos.md)\n- [GLM-5.3 vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.md)\n- [GLM-5.3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.md)\n- [GLM-5.3 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1.md)\n- [GLM-5.3 vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-lbs-27b.md)\n- [GLM-5.3 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b.md)\n- [GLM-5.3 vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b.md)\n- [GLM-5.3 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-audio-2b.md)\n- [GLM-5.3 vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-omni-2b.md)\n- [GLM-5.3 vs LFM3-VL-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-vl-2b.md)\n- [GLM-5.3 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny.md)\n- [GLM-5.3 vs LongCat-2.5](https://www.anchorterminal.com/compare/glm-5-3-vs-longcat-2-5.md)\n- [GLM-5.3 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-5.3 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-flash-rl.md)\n- [GLM-5.3 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.md)\n- [GLM-5.3 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-1b.md)\n- [GLM-5.3 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-35b-a3b.md)\n- [GLM-5.3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.md)\n- [GLM-5.3 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.md)\n- [GLM-5.3 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7.md)\n- [GLM-5.3 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m3-1-flash.md)\n- [GLM-5.3 vs Mistral Large 4](https://www.anchorterminal.com/compare/glm-5-3-vs-mistral-large-4.md)\n- [GLM-5.3 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b.md)\n- [GLM-5.3 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-2-3b.md)\n- [GLM-5.3 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/glm-5-3-vs-nanbeige-4-3-33b.md)\n- [GLM-5.3 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [GLM-5.3 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [GLM-5.3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-5.3 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b.md)\n- [GLM-5.3 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [GLM-5.3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-5.3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-5.3 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-5-3-vs-north-mini-code-1-0.md)\n- [GLM-5.3 vs occamy-1.0](https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.md)\n- [GLM-5.3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think.md)\n- [GLM-5.3 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b.md)\n- [GLM-5.3 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b.md)\n- [GLM-5.3 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b.md)\n- [GLM-5.3 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b.md)\n- [GLM-5.3 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/glm-5-3-vs-otel-2-0-llm-31b-it.md)\n- [GLM-5.3 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen-agentworld-35b-a3b.md)\n- [GLM-5.3 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507.md)\n- [GLM-5.3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507.md)\n- [GLM-5.3 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b.md)\n- [GLM-5.3 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b.md)\n- [GLM-5.3 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b.md)\n- [GLM-5.3 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b.md)\n- [GLM-5.3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b.md)\n- [GLM-5.3 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b.md)\n- [GLM-5.3 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b.md)\n- [GLM-5.3 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b.md)\n- [GLM-5.3 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b.md)\n- [GLM-5.3 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next.md)\n- [GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next.md)\n- [GLM-5.3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct.md)\n- [GLM-5.3 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2.md)\n- [GLM-5.3 vs Recursive Flint](https://www.anchorterminal.com/compare/glm-5-3-vs-recursive-flint.md)\n- [GLM-5.3 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-ripple-65b-preview.md)\n- [GLM-5.3 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-sensenova-loop-9b-preview.md)\n- [GLM-5.3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.md)\n- [GLM-5.3 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b.md)\n- [GLM-5.3 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/glm-5-3-vs-step-3-7-flash.md)\n- [GLM-5.3 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b.md)\n- [GLM-5.3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b.md)\n- [GLM-5.3 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/glm-5-3-vs-unlimited-ocr-2.md)\n- [GLM-5.3 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-2b.md)\n- [GLM-5.3 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-wevisone-vl-4b.md)\n- [GLM-5.3 vs ZAYA1-8B](https://www.anchorterminal.com/compare/glm-5-3-vs-zaya1-8b.md)\n- [gpt-oss-120b vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-1-flash-1019.md)\n- [gpt-oss-20b vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ling-3-1-flash-1019.md)\n- [Granite 4.2 30B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019.md)\n- [Granite 4.2 3B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ling-3-1-flash-1019.md)\n- [Granite 4.2 8B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ling-3-1-flash-1019.md)\n- [Hy-Memory-30B-A3B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ling-3-1-flash-1019.md)\n- [Hy3 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/hy3-vs-ling-3-1-flash-1019.md)\n- [Inkling-Small vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-1-flash-1019.md)\n- [Inkling vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/inkling-vs-ling-3-1-flash-1019.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ling-3-1-flash-1019.md)\n- [Kimi K3.1 Pro vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ling-3-1-flash-1019.md)\n- [Kimi K3 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-1-flash-1019.md)\n- [Kolibri-1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/kolibri-1-vs-ling-3-1-flash-1019.md)\n- [Kronos vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/kronos-vs-ling-3-1-flash-1019.md)\n- [Laguna M.1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019.md)\n- [Laguna S 2.1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-1-flash-1019.md)\n- [Laguna XS 2.1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-1-flash-1019.md)\n- [LBS-27B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lbs-27b-vs-ling-3-1-flash-1019.md)\n- [LFM2.5-2.6B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ling-3-1-flash-1019.md)\n- [LFM3-1.7B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019.md)\n- [LFM3-Audio-2B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ling-3-1-flash-1019.md)\n- [LFM3-Omni-2B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ling-3-1-flash-1019.md)\n- [LFM3-VL-2B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ling-3-1-flash-1019.md)\n- [Ling-3.0-tiny vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ling-3-1-flash-1019.md)\n- [Ling-3.1-flash-1019 vs LongCat-2.5](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-longcat-2-5.md)\n- [Ling-3.1-flash-1019 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Ling-3.1-flash-1019 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mimo-v2-6-flash-rl.md)\n- [Ling-3.1-flash-1019 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-o-4-5.md)\n- [Ling-3.1-flash-1019 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-1b.md)\n- [Ling-3.1-flash-1019 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm-v-4-7-35b-a3b.md)\n- [Ling-3.1-flash-1019 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minicpm5-2b.md)\n- [Ling-3.1-flash-1019 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-5.md)\n- [Ling-3.1-flash-1019 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m2-7.md)\n- [Ling-3.1-flash-1019 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-minimax-m3-1-flash.md)\n- [Ling-3.1-flash-1019 vs Mistral Large 4](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-mistral-large-4.md)\n- [Ling-3.1-flash-1019 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-muse-glimmer-30b.md)\n- [Ling-3.1-flash-1019 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-2-3b.md)\n- [Ling-3.1-flash-1019 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-3-33b.md)\n- [Ling-3.1-flash-1019 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-30b-a3b.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-super-120b-a12b.md)\n- [Ling-3.1-flash-1019 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-ultra-550b-a55b.md)\n- [Ling-3.1-flash-1019 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-north-mini-code-1-0.md)\n- [Ling-3.1-flash-1019 vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-occamy-1-0.md)\n- [Ling-3.1-flash-1019 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-olmo-3-7b-think.md)\n- [Ling-3.1-flash-1019 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b.md)\n- [Ling-3.1-flash-1019 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-35b-a3b.md)\n- [Ling-3.1-flash-1019 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-397b.md)\n- [Ling-3.1-flash-1019 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-9b.md)\n- [Ling-3.1-flash-1019 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-otel-2-0-llm-31b-it.md)\n- [Ling-3.1-flash-1019 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen-agentworld-35b-a3b.md)\n- [Ling-3.1-flash-1019 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Ling-3.1-flash-1019 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-4b-instruct-2507.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-0-8b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-122b-a10b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-2b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-397b-a17b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-4b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-9b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-27b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-6-35b-a3b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-27b.md)\n- [Ling-3.1-flash-1019 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next.md)\n- [Ling-3.1-flash-1019 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-next.md)\n- [Ling-3.1-flash-1019 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-2b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-32b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-4b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-vl-8b-instruct.md)\n- [Ling-3.1-flash-1019 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwopus3-8-27b-flash-v2.md)\n- [Ling-3.1-flash-1019 vs Recursive Flint](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-recursive-flint.md)\n- [Ling-3.1-flash-1019 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ripple-65b-preview.md)\n- [Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview.md)\n- [Ling-3.1-flash-1019 vs SmolLM3-3B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-smollm3-3b.md)\n- [Ling-3.1-flash-1019 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-spark-x2-6-4b.md)\n- [Ling-3.1-flash-1019 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-step-3-7-flash.md)\n- [Ling-3.1-flash-1019 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-27b.md)\n- [Ling-3.1-flash-1019 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ling-3.1-flash-1019 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-thinkingcap-qwen3-8-27b.md)\n- [Ling-3.1-flash-1019 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-unlimited-ocr-2.md)\n- [Ling-3.1-flash-1019 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-2b.md)\n- [Ling-3.1-flash-1019 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-wevisone-vl-4b.md)\n- [Ling-3.1-flash-1019 vs ZAYA1-8B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.md)\n",
  "meta": {
    "attribution": "Anchor Terminal (https://www.anchorterminal.com)",
    "attributionRequired": true,
    "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)",
    "docs": "https://www.anchorterminal.com/docs/",
    "generatedAt": "2026-11-11",
    "license": "CC-BY-4.0",
    "method": "https://www.anchorterminal.com/benchmark/",
    "methodology": "0.7",
    "openapi": "https://www.anchorterminal.com/openapi.json",
    "preview": false,
    "run": "2026-10-01",
    "runLabel": "October 2026 research run",
    "terms": "https://www.anchorterminal.com/terms/#data"
  },
  "page": {
    "breadcrumbs": [
      {
        "name": "Home",
        "url": "https://www.anchorterminal.com/"
      },
      {
        "name": "Compare",
        "url": "https://www.anchorterminal.com/compare/"
      },
      {
        "name": "GLM-5.3 vs Ling-3.1-flash-1019",
        "url": ""
      }
    ],
    "description": "GLM-5.3 scores 64.6 (B) to Ling-3.1-flash-1019's 54.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
    "facts": [
      "GLM-5.3 B 64.6",
      "Ling-3.1-flash-1019 C 54.8",
      "scores"
    ],
    "h1": "GLM-5.3 vs Ling-3.1-flash-1019",
    "image": "https://www.anchorterminal.com/assets/og/default.png",
    "path": "/compare/glm-5-3-vs-ling-3-1-flash-1019",
    "published": "2026-10-01",
    "section": "tools",
    "title": "GLM-5.3 vs Ling-3.1-flash-1019 for AI agents (2026) | Anchor Terminal",
    "toc": null,
    "updated": "2026-11-10",
    "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-1-flash-1019"
  },
  "tokens": {
    "markdown": 9350,
    "slim": 730
  },
  "version": 1
}