{
  "data": {
    "a": {
      "slug": "glm-5-3-flash",
      "name": "GLM-5.3-Flash",
      "vendor": "Z.ai (Zhipu AI)",
      "vendorUrl": "https://z.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "GLM-5.3-Flash is Z.ai's open-weight multimodal mixture-of-experts model, 320B parameters with 18B active and a 1,048,576-token context, published on Hugging Face in FP8 and BF16 under the MIT licence.",
      "url": "https://www.anchorterminal.com/tools/glm-5-3-flash",
      "markdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json",
      "dns": "glm-5-3-flash.grade.anchorterminal.com",
      "repo": "https://huggingface.co/zai-org/GLM-5.3-Flash",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "zai-org/GLM-5.3-Flash"
        },
        {
          "registry": "huggingface",
          "name": "zai-org/GLM-5.3-Flash-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 MIT licence. Z.ai also sells hosted access as glm-5.3-flash on its own API, which isn't graded here. Running the weights yourself costs the hardware, 328.4 GB for the FP8 files and 642.7 GB for BF16 (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-Flash",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "mit",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-08-26",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 65.1,
        "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": 1524,
        "categoryRank": 13,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "capability": 75,
          "interface": 70,
          "reach": 60,
          "risk": 55,
          "upkeep": 58
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-02"
        },
        "negative": 0,
        "verdict": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.",
        "bestFor": "Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider",
        "strengths": [
          "MIT weights with no use policy, downloadable with no account",
          "Model code in released llama.cpp b11768, vLLM 0.32.0, SGLang 0.5.22 and Transformers 5.16.1",
          "Safetensors only, no remote code, files in Z.ai's own organisation with a SHA-256 per shard",
          "1,048,576 tokens of native context and several tool calls per turn in the chat template",
          "Chat template changed as recently as 15 October 2026, and hosted by Z.ai and six other providers for agents without the hardware"
        ],
        "weaknesses": [
          "Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists",
          "No safety evaluation, agent-use guidance or security contact",
          "Thinking is always on, and reasoning_effort only lowers it to low",
          "The tool-call format lives only in the chat template, with the parser named by the runtimes",
          "The card leaves out intended use, limitations, context length and knowledge cut-off, and no zai-org reply on discussions since 28 September"
        ],
        "agentNotes": [
          "Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)",
          "Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs",
          "Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max",
          "Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block",
          "Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt",
          "On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 65.1
          }
        ],
        "editorialScores": {
          "capability": 75,
          "interface": 70,
          "reach": 60,
          "risk": 55,
          "upkeep": 58
        },
        "provenanceScore": 61,
        "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 0.32.0 or later, per vLLM's recipe (FP8, about 386 GB of GPU memory)\nvllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 \\\n  --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47\n# or, with llama.cpp and llama.cpp's own GGUF:\nllama-server -hf ggml-org/GLM-5.3-Flash-GGUF:Q4_K --jinja",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"zai-org/GLM-5.3-Flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"reasoning_effort\": \"low\"}}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/glm-5-3-flash"
      },
      "sameCompany": [
        "glm-4-5-air",
        "glm-4-7-flash",
        "glm-5-3"
      ],
      "weights": {
        "trainedBy": "Z.ai",
        "params": "320B",
        "active": "18B",
        "context": 1048576,
        "goodFor": "Multimodal agent and coding model: text, images and video in, text out, with tool calling and always-on reasoning.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "GLM-5.3-Flash-FP4-Local",
            "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-FP4-Local",
            "who": "NVIDIA",
            "precision": "nvfp4",
            "sizeGB": 177.5,
            "memoryGB": 256,
            "format": "safetensors",
            "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026."
          },
          {
            "name": "GLM-5.3-Flash-NVFP4",
            "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-NVFP4",
            "who": "NVIDIA",
            "precision": "nvfp4",
            "sizeGB": 204.4,
            "memoryGB": 256,
            "format": "safetensors",
            "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026."
          },
          {
            "name": "ggml-org GLM-5.3-Flash-GGUF (Q4_K)",
            "url": "https://huggingface.co/ggml-org/GLM-5.3-Flash-GGUF",
            "who": "llama.cpp",
            "precision": "q4_k",
            "sizeGB": 182.03,
            "memoryGB": 256,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From ggml-org, the llama.cpp project's organisation. 181.37 GB of Q4_K weights plus the 0.65 GB Q8_0 vision projector, from the Hub's model information on 10 November 2026. The 2-bit files (Q2_K 133.8 GB, Q2_K_S 110.0 GB) are below the 4-bit line and aren't listed. Recorded after the last grading, so Reach doesn't count it yet"
          },
          {
            "name": "GLM-5.3-Flash",
            "url": "https://huggingface.co/zai-org/GLM-5.3-Flash",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 328.3,
            "memoryGB": 512,
            "format": "safetensors"
          },
          {
            "name": "GLM-5.3-Flash-BF16",
            "url": "https://huggingface.co/zai-org/GLM-5.3-Flash-BF16",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 642.7,
            "memoryGB": 1024,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          }
        ],
        "run": "vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47",
        "runBuild": "GLM-5.3-Flash",
        "checked": "2026-10-21",
        "minMemoryGB": 256
      },
      "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",
            "url": "https://huggingface.co/zai-org/GLM-5.3",
            "params": "744B-A40B",
            "listing": "https://www.anchorterminal.com/tools/glm-5-3"
          }
        ],
        "olderCount": 19,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Z.AI Co., Ltd (named in the licence's copyright line)",
        "domain": "z.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/zai-org/GLM-5.3-Flash/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE file reads Copyright (c) 2026 Z.AI Co., Ltd. The registration date of z.ai couldn't be read, since the RDAP service answered 429 on 21 October 2026.",
          "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history. Early messages say only \"update\"; later ones say what changed (a chat template fix on 4 September, evaluation results on 7 September and 12 October, a chat template speed-up on 15 October).",
          "z.ai/.well-known/security.txt and docs.z.ai/.well-known/security.txt answered 404 on 21 October 2026."
        ],
        "score": 61
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.json",
      "live": {
        "slug": "glm-5-3-flash",
        "securityTxt": {
          "url": "https://z.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-14T16:18:35.100157195Z"
        },
        "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-Flash/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-14T19:07:52.068228874Z",
            "changedAt": "2026-11-14T19:07:52.068228874Z",
            "fingerprint": "e562e58efad5"
          }
        ],
        "updatedAt": "2026-11-14T19:07:52.068228874Z"
      }
    },
    "answer": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.",
    "b": {
      "slug": "inkling-2-small",
      "name": "Inkling 2 Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling 2 Small is Thinking Machines Lab's open-weight mixture-of-experts model, 594B total and 17B active parameters, taking text and images and returning text, with adjustable thinking effort, published in NVFP4 and MXFP8 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling-2-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json",
      "dns": "inkling-2-small.grade.anchorterminal.com",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small-MXFP8"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-11-12). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 393.5 GB of files for the NVFP4 checkpoint and 622.8 GB for MXFP8, which Thinking Machines puts at 500 GB and 800 GB of GPU memory. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens, $0.03 cached and $1.00 output (read 2026-11-06).",
      "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 2026-11-12).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-12"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-2-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-11-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.8,
        "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": 1524,
        "categoryRank": 78,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-12"
        },
        "negative": 0,
        "verdict": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
        "bestFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "strengths": [
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to xhigh, several tool calls a turn and a 1M-token context",
          "Two checkpoints from Thinking Machines, NVFP4 and MXFP8, under Apache 2.0 with no gate",
          "Thinking Machines' tml-renderers package renders prompts and parses tool calls for this model",
          "A training-content summary with sources, mix and an October 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference, and the card names seven more API providers"
        ],
        "weaknesses": [
          "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory",
          "No released version of vLLM, SGLang, Transformers, llama.cpp or Ollama runs it on 12 November 2026",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance",
          "Structured output isn't documented, and the card gives no dated knowledge cut-off",
          "No independent benchmark results were read, so Capability is pending and the total is capped at 61"
        ],
        "agentNotes": [
          "No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image",
          "In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`",
          "Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99",
          "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026",
          "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.8
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "provenanceScore": 72,
        "checked": {
          "categories": {
            "interface": "2026-11-12",
            "reach": "2026-11-12",
            "risk": "2026-11-12",
            "upkeep": "2026-11-12"
          },
          "last": "2026-11-12",
          "lastMoved": "2026-11-12",
          "oldest": "2026-11-12",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, the NVFP4 checkpoint on 4 B300 GPUs. Not in an SGLang release yet,\n# so run it inside the lmsysorg/sglang:dev-inkling-2-small image:\nSGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve \\\n  --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 \\\n  --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 \\\n  --page-size 128 --grammar-backend xgrammar --enable-multimodal \\\n  --reasoning-parser inkling --tool-call-parser inkling2",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-2-Small\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling-2-small"
      },
      "sameCompany": [
        "inkling",
        "inkling-small"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "594B",
        "active": "17B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images in, a 1M-token context and thinking effort set per request.",
        "runtimes": [],
        "builds": [
          {
            "name": "Inkling-2-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 393.5,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "The main checkpoint, in the precision the model was trained in. Routed experts in NVFP4 for layers 0 to 39 and MXFP8 for layers 40 to 47, per SGLang's cookbook. Thinking Machines states at least 500 GB of GPU memory"
          },
          {
            "name": "Inkling-2-Small-MXFP8",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small-MXFP8",
            "who": "publisher",
            "precision": "mxfp8",
            "sizeGB": 622.8,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Every routed expert in MXFP8. Thinking Machines states at least 800 GB of GPU memory and recommends the NVFP4 checkpoint. It's the only checkpoint Transformers' main branch loads"
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        ],
        "run": "SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 --page-size 128 --grammar-backend xgrammar --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling2",
        "runBuild": "Inkling-2-Small",
        "checked": "2026-11-12",
        "minMemoryGB": 512
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      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling 2",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named as provider on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling-2-Small/commits/main",
        "securityTxt": "valid",
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        "notes": [
          "Thinking Machines' model card page links both repositories in the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 3 commits on 12 November 2026, the upload, a library tag from a merged pull request and a card update.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, read on 12 November 2026, and the model card page links a coordinated vulnerability disclosure policy.",
          "Thinking Machines' terms bar scraping the Services. The founder decided on 6 November 2026 that reading at a person's pace is fine, so six pages were read one at a time on 12 November: the acceptable use policy, the training data page and its summary for this model, the model card page, and the tml-renderers and thinking effort guides. thinkingmachines.ai's robots.txt has no rules, and tinker-docs.thinkingmachines.ai answers 404 for robots.txt."
        ],
        "score": 72
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      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-2-small.json",
      "live": {
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          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 439,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
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          "p95ms24h": 467,
          "samples24h": 245,
          "samples30d": 1854,
          "days": [
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              "probes": 186,
              "ok": 186
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              "date": "2026-11-07",
              "probes": 243,
              "ok": 243
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              "ok": 243
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              "date": "2026-11-09",
              "probes": 243,
              "ok": 243
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            {
              "date": "2026-11-10",
              "probes": 244,
              "ok": 244
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            {
              "date": "2026-11-11",
              "probes": 244,
              "ok": 244
            },
            {
              "date": "2026-11-12",
              "probes": 245,
              "ok": 245
            },
            {
              "date": "2026-11-13",
              "probes": 206,
              "ok": 206
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          ],
          "since": "2026-11-06T00:00:00Z"
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        "securityTxt": {
          "url": "https://thinkingmachines.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2029-07-13T07:00:00.000Z",
          "checkedAt": "2026-11-14T16:19:22.779006645Z"
        },
        "llmsTxt": {
          "url": "https://tinker-docs.thinkingmachines.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-13T15:54:36.79283015Z"
        },
        "domain": {
          "domain": "thinkingmachines.ai",
          "registered": "2024-07-09",
          "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai",
          "checkedAt": "2026-11-08T15:05:10.558189316Z"
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        "pages": [
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            "checkedAt": "2026-11-13T18:32:53.884197991Z",
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            "fingerprint": "3c33a4a74c61"
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            "url": "https://thinkingmachines.ai/legal/terms/",
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      "streak": {
        "days": 9,
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        "sinceWatching": true,
        "best": 9
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      {
        "by": 20,
        "category": "reach",
        "leads": "glm-5-3-flash",
        "name": "Reach",
        "reasons": {
          "a": "Memory earns nothing, since Z.ai's smallest build is the 328.4 GB FP8 one, about 394 GB with the fifth added, and neither Ollama nor LM Studio has a local build (both list it as cloud only). Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio don't. Z.ai publishes one quantised build, FP8, for 10. The MIT licence with nothing added gives the full 15, the files download with no account or gate for 10, and Z.ai's own API plus six providers on Hugging Face serve it, for 5.",
          "b": "Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40."
        },
        "scores": {
          "a": 60,
          "b": 40
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      },
      {
        "by": 15,
        "category": "interface",
        "leads": "inkling-2-small",
        "name": "Agent interface",
        "reasons": {
          "a": "A Jinja chat template sits in both repositories, for 20. The tool-calling format is 10, because 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 only the hosted API documented for JSON. Reasoning control is 10, a per-request budget through reasoning_effort, with the reasoning coming back in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rotary scaling.",
          "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85."
        },
        "scores": {
          "a": 70,
          "b": 85
        }
      },
      {
        "by": 10,
        "category": "risk",
        "leads": "inkling-2-small",
        "name": "Risk",
        "reasons": {
          "a": "File safety is full, with safetensors only, no Python and no remote code needed in Transformers 5.16.1 or later. Provenance is full, files in the zai-org organisation Z.ai links from GitHub with a SHA-256 for every shard. Safety evaluation and agent guidance are 0, as nothing is published on either. Licence risk is the full 15, since MIT adds no policy, threshold or changeable terms. The security programme is 0, with no security.txt on z.ai or docs.z.ai, no SECURITY.md on GitHub and no advisories found.",
          "b": "File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65."
        },
        "scores": {
          "a": 55,
          "b": 65
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        "by": 9,
        "category": "upkeep",
        "leads": "inkling-2-small",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 5, a 30T-token corpus described with no sources or cut-off. The last change, a chat template speed-up on 15 October in both repositories, is within 30 days on 2 November, for 20; Z.ai's GLM-5 GitHub repository has changed only its docs since. Responsiveness is 10, as zai-org answered 14 of the 38 recent discussions others opened (26 August to 30 October), the last on 28 September, which is some but not most. Version policy is 5 for a first release, and file health is the full 10, with files and card agreeing and no broken-file report waiting as far as the research record shows.",
          "b": "Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67."
        },
        "scores": {
          "a": 58,
          "b": 67
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        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
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      {
        "a": "Z.ai (Zhipu AI)",
        "b": "Thinking Machines Lab",
        "name": "Vendor"
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      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
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      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
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      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
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      {
        "a": "MIT",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-08-26",
        "b": "2026-11-12",
        "name": "Last release"
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        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
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      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "2.8/5 (4)",
        "b": "none",
        "name": "Agent reviews"
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    ],
    "faq": [
      {
        "answer": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.",
        "question": "Which is better for AI agents, GLM-5.3-Flash or Inkling 2 Small?"
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    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 60 against 40"
        ],
        "also": null,
        "goodFor": "Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider",
        "slug": "glm-5-3-flash",
        "watchFor": "Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists"
      },
      {
        "aheadOn": [
          "Risk, 65 against 55",
          "Agent interface, 85 against 70",
          "Documentation and upkeep, 67 against 58"
        ],
        "also": null,
        "goodFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "slug": "inkling-2-small",
        "watchFor": "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory"
      }
    ],
    "history": {
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      "inkling-2-small": [
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          "delta": 6.7,
          "from": 52.1,
          "fromGrade": "D",
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          "toGrade": "C"
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-4b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Inkling 2 Small vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Inkling 2 Small vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0.json",
        "title": "Inkling 2 Small vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0.json",
        "title": "Inkling 2 Small vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think.json",
        "title": "Inkling 2 Small vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b.json",
        "title": "Inkling 2 Small vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-otel-2-0-llm-31b-it.json",
        "title": "Inkling 2 Small vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b.json",
        "title": "Inkling 2 Small vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Inkling 2 Small vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.json",
        "title": "Inkling 2 Small vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.json",
        "title": "Inkling 2 Small vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b.json",
        "title": "Inkling 2 Small vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b.json",
        "title": "Inkling 2 Small vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b.json",
        "title": "Inkling 2 Small vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b.json",
        "title": "Inkling 2 Small vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b.json",
        "title": "Inkling 2 Small vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.json",
        "title": "Inkling 2 Small vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.json",
        "title": "Inkling 2 Small vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.json",
        "title": "Inkling 2 Small vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Inkling 2 Small vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint.json",
        "title": "Inkling 2 Small vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview.json",
        "title": "Inkling 2 Small vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview.json",
        "title": "Inkling 2 Small vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.json",
        "title": "Inkling 2 Small vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b.json",
        "title": "Inkling 2 Small vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash.json",
        "title": "Inkling 2 Small vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2.json",
        "title": "Inkling 2 Small vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.json",
        "title": "Inkling 2 Small vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b.json",
        "title": "Inkling 2 Small vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b.json",
        "title": "Inkling 2 Small vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small.json",
        "title": "Inkling vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 20,
        "edge": "glm-5-3-flash",
        "glm-5-3-flash": 60,
        "inkling-2-small": 40,
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 10,
        "edge": "inkling-2-small",
        "glm-5-3-flash": 55,
        "inkling-2-small": 65,
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 15,
        "edge": "inkling-2-small",
        "glm-5-3-flash": 70,
        "inkling-2-small": 85,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 9,
        "edge": "inkling-2-small",
        "glm-5-3-flash": 58,
        "inkling-2-small": 67,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "glm-5-3-flash": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.",
      "inkling-2-small": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small",
    "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.min.md"
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  "markdown": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.\n\n- GLM-5.3-Flash: grade B, 65.1/100, rank #18 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-5-3-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json\n- Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.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 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### GLM-5.3-Flash (B)\n\nGood for: Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider\n\nAhead on:\n- Reach, 60 against 40\n\nWatch for: Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists\n\n### Inkling 2 Small (C)\n\nGood for: Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.\n\nAhead on:\n- Risk, 65 against 55\n- Agent interface, 85 against 70\n- Documentation and upkeep, 67 against 58\n\nWatch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory\n\n\n## Why the edge\n\n### Reach: GLM-5.3-Flash +20\n\n- GLM-5.3-Flash (60): Memory earns nothing, since Z.ai's smallest build is the 328.4 GB FP8 one, about 394 GB with the fifth added, and neither Ollama nor LM Studio has a local build (both list it as cloud only). Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio don't. Z.ai publishes one quantised build, FP8, for 10. The MIT licence with nothing added gives the full 15, the files download with no account or gate for 10, and Z.ai's own API plus six providers on Hugging Face serve it, for 5.\n- Inkling 2 Small (40): Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.\n\n### Agent interface: Inkling 2 Small +15\n\n- GLM-5.3-Flash (70): A Jinja chat template sits in both repositories, for 20. The tool-calling format is 10, because 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 only the hosted API documented for JSON. Reasoning control is 10, a per-request budget through reasoning_effort, with the reasoning coming back in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rotary scaling.\n- Inkling 2 Small (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n\n### Risk: Inkling 2 Small +10\n\n- GLM-5.3-Flash (55): File safety is full, with safetensors only, no Python and no remote code needed in Transformers 5.16.1 or later. Provenance is full, files in the zai-org organisation Z.ai links from GitHub with a SHA-256 for every shard. Safety evaluation and agent guidance are 0, as nothing is published on either. Licence risk is the full 15, since MIT adds no policy, threshold or changeable terms. The security programme is 0, with no security.txt on z.ai or docs.z.ai, no SECURITY.md on GitHub and no advisories found.\n- Inkling 2 Small (65): File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65.\n\n### Documentation and upkeep: Inkling 2 Small +9\n\n- GLM-5.3-Flash (58): The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 5, a 30T-token corpus described with no sources or cut-off. The last change, a chat template speed-up on 15 October in both repositories, is within 30 days on 2 November, for 20; Z.ai's GLM-5 GitHub repository has changed only its docs since. Responsiveness is 10, as zai-org answered 14 of the 38 recent discussions others opened (26 August to 30 October), the last on 28 September, which is some but not most. Version policy is 5 for a first release, and file health is the full 10, with files and card agreeing and no broken-file report waiting as far as the research record shows.\n- Inkling 2 Small (67): Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.\n\n## Score by category\n\n| Category | Weight | GLM-5.3-Flash | Inkling 2 Small | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 40 | GLM-5.3-Flash +20 |\n| Risk | 20% (20 this run) | 55 | 65 | Inkling 2 Small +10 |\n| Agent interface | 10% (10 this run) | 70 | 85 | Inkling 2 Small +15 |\n| Documentation and upkeep | 10% (10 this run) | 58 | 67 | Inkling 2 Small +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.1 · B** | **58.8 · C** | |\n\n## Facts side by side\n\n| Fact | GLM-5.3-Flash | Inkling 2 Small |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Z.ai (Zhipu AI) | Thinking Machines Lab |\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 | MIT | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-26 | 2026-11-12 |\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## How the scores have moved\n\n### GLM-5.3-Flash\n\nNo score change since it was listed.\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n## Verdicts\n\n**GLM-5.3-Flash.** An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.\n\n**Inkling 2 Small.** Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.\n\n## Before you call either\n\n### GLM-5.3-Flash\n\n1. Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)\n2. Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs\n3. Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max\n4. Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block\n5. Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt\n6. On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai\n\n### Inkling 2 Small\n\n1. No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image\n2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`\n3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet\n4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99\n5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part\n8. Use guided decoding or validate JSON yourself, since structured output isn't documented\n9. Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026\n10. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n## Questions\n\n### Which is better for AI agents, GLM-5.3-Flash or Inkling 2 Small?\n\nGLM-5.3-Flash scores 65.1 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"glm-5-3-flash\", \"b\": \"inkling-2-small\"}`. 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