{
  "data": {
    "a": {
      "slug": "darwin-36b-opus",
      "name": "Darwin-36B-Opus",
      "vendor": "FINAL-Bench (VIDRAFT)",
      "vendorUrl": "https://vidraft.net",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Darwin-36B-Opus is VIDRAFT's open-weight text-only mixture-of-experts reasoning model, about 35B parameters with about 3B active per token, made by merging Qwen3.6-35B-A3B with a reasoning-distilled fine-tune of it, published in BF16 and GGUF and marked Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/darwin-36b-opus",
      "markdownUrl": "https://www.anchorterminal.com/tools/darwin-36b-opus.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/darwin-36b-opus.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json",
      "dns": "darwin-36b-opus.grade.anchorterminal.com",
      "repo": "https://huggingface.co/FINAL-Bench/Darwin-36B-Opus",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "FINAL-Bench/Darwin-36B-Opus"
        },
        {
          "registry": "huggingface",
          "name": "FINAL-Bench/POCKET-35B-GGUF"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither the main repository nor the POCKET-35B-GGUF build is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the Apache 2.0 licence named in the card's metadata. The repository has held an Apache 2.0 LICENSE file since 1 November 2026. Running it yourself costs the hardware, about 69 GB for the BF16 files or 21.2 GB for the publisher's Q4_K_M GGUF (checked 2026-11-03).",
      "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": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/FINAL-Bench/Darwin-36B-Opus",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "merge",
        "derivative",
        "apache-2.0",
        "safetensors",
        "gguf",
        "self-hosted"
      ],
      "lastRelease": "2026-04-23",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "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": 33,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 80,
          "risk": 55,
          "upkeep": 61
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-03"
        },
        "negative": 0,
        "verdict": "A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.",
        "bestFor": "Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required",
        "strengths": [
          "Runs in released vLLM, SGLang, Transformers and llama.cpp as the text-only Qwen3.5 MoE architecture",
          "The publisher's Q4_K_M GGUF fits in 32 GB, with about 3B active parameters per token",
          "Apache 2.0 through the whole licence chain, with a LICENSE file since 1 November 2026 and no gate",
          "Safetensors and GGUF only, with a SHA-256 on every weight file in the publisher's own organisation",
          "The publisher answered 8 of the 13 discussions"
        ],
        "weaknesses": [
          "The merge method is proprietary and the current weights include an undescribed targeted refinement",
          "No safety results, agent guidance or security contact",
          "The card's head counts and base disagree with the files",
          "Tool calling and structured output aren't documented, and the card names no parser",
          "The files were replaced in place on the first day with no note on the card"
        ],
        "agentNotes": [
          "Quickest start is `llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja`, about 21 GB of files",
          "On the reference machine BF16 fits, `vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parsers for Qwen3.6's format",
          "Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention",
          "The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces",
          "generation_config.json stops only on the end-of-text token, so add `\u003c|im_end|\u003e` as a stop token if a runtime keeps generating after the turn ends",
          "Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files",
          "Validate JSON output yourself, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 80,
          "risk": 55,
          "upkeep": 61
        },
        "provenanceScore": 44,
        "checked": {
          "categories": {
            "interface": "2026-11-03",
            "reach": "2026-11-03",
            "risk": "2026-11-03",
            "upkeep": "2026-11-03"
          },
          "last": "2026-11-03",
          "lastMoved": "2026-11-03",
          "oldest": "2026-11-03",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja -c 32768\n# or the BF16 weights with vLLM:\nvllm serve FINAL-Bench/Darwin-36B-Opus --max-model-len 262144 --reasoning-parser qwen3 \\\n  --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "http": "curl http://localhost:8080/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/darwin-36b-opus"
      },
      "weights": {
        "trainedBy": "FINAL-Bench (VIDRAFT)",
        "builtOn": "A merge of Qwen/Qwen3.6-35B-A3B (Apache 2.0) as the base and hesamation/Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled (Apache 2.0, a LoRA fine-tune of the same base on reasoning traces mostly from Claude Opus 4.6), per the card's text. The metadata declared both as base_model until 3 June 2026 and declares none now. Text-only, the base without its vision encoder",
        "params": "35B (3B active)",
        "active": "3B",
        "context": 262144,
        "goodFor": "Text-only mixture-of-experts reasoning model merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, thinking on by default, fast for its size with about 3B active parameters.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "POCKET-35B-IQ1_M",
            "url": "https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF/blob/main/POCKET-35B-IQ1_M.gguf",
            "who": "publisher",
            "precision": "iq1_m",
            "sizeGB": 8.2,
            "memoryGB": 12,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Below 4-bit, so it doesn't count for the memory line"
          },
          {
            "name": "POCKET-35B-Q2_K",
            "url": "https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF/blob/main/POCKET-35B-Q2_K.gguf",
            "who": "publisher",
            "precision": "q2_k",
            "sizeGB": 12.9,
            "memoryGB": 16,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Below 4-bit, so it doesn't count for the memory line"
          },
          {
            "name": "POCKET-35B-Q3_K_M",
            "url": "https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF/blob/main/POCKET-35B-Q3_K_M.gguf",
            "who": "publisher",
            "precision": "q3_k_m",
            "sizeGB": 16.8,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Below 4-bit, so it doesn't count for the memory line"
          },
          {
            "name": "POCKET-35B-Q4_K_M",
            "url": "https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF/blob/main/POCKET-35B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 21.2,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "Darwin-36B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-36B-Opus",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 69.4,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ]
          }
        ],
        "run": "vllm serve FINAL-Bench/Darwin-36B-Opus --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "runBuild": "Darwin-36B-Opus",
        "checked": "2026-10-21",
        "minMemoryGB": 12
      },
      "family": {
        "lab": "FINAL-Bench (VIDRAFT)",
        "family": "Darwin",
        "url": "https://www.anchorterminal.com/open-weights/#final-bench",
        "others": [
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            "name": "Darwin-35B-A3B-Opus",
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          },
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            "name": "Darwin-2B-webgpu",
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          },
          {
            "name": "Darwin-4B-David",
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            "name": "Darwin-TTS-1.7B-Cross",
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            "name": "Darwin-2B-Opus",
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            "name": "Darwin-28B-NEG",
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            "name": "Darwin-9B-NEG",
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            "name": "Darwin-28B-KR-Legal",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-KR-Legal",
            "params": "28B (26,895,998,464 by the Hub's safetensors count)"
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            "name": "Darwin-9B-NEG-x-Negentropy-V8",
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            "name": "Darwin-Mistral-G1",
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            "name": "Darwin-28B-REASON",
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            "name": "Darwin-28B-Coder",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-Coder",
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          },
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            "name": "Darwin-218B-Delphi",
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          },
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            "name": "Darwin-218B-Expert-Bio",
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            "name": "Darwin-60B-DUO",
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            "params": "60B (two ~30B models together)"
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            "name": "Darwin-397B-JGOS",
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            "params": "397B total, 17B active (MoE; 403,397,928,944 by the Hub's safetensors count)"
          },
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            "name": "Darwin-398B-JGOS",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-398B-JGOS",
            "params": "398B (MoE; 403,397,928,944 by the Hub's safetensors count)"
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          {
            "name": "Darwin-Chimera-4B-Gen1",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-Chimera-4B-Gen1",
            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
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            "name": "Darwin-V9-Chimera-4B",
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            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
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            "name": "Darwin-V9-Chimera-4B-SFT",
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            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
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            "name": "Darwin-36B-KR",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-36B-KR",
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            "name": "Darwin-397B-ZTC",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-397B-ZTC",
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          },
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            "name": "Darwin-4B-Chimera",
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            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
          },
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            "name": "Darwin-Chimera-4B-MoE-2E-PoC",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-Chimera-4B-MoE-2E-PoC",
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            "name": "Darwin-V9-Chimera-4B-MoE3",
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            "name": "Darwin-27B-RSI",
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            "params": "27B (26,895,998,464 by the Hub's safetensors count)"
          },
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            "name": "Darwin-180B-RSI",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-180B-RSI",
            "params": "180B (MoE; 179,999,981,459 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-180B-RSI-R3",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-180B-RSI-R3",
            "params": "180B (MoE; 179,999,981,459 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-ZTC",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-ZTC",
            "params": "27B (25,624,600,064 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-ZTC-v2",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-ZTC-v2",
            "params": "27B (25,624,600,064 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-ZTC-v5",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-ZTC-v5",
            "params": "27B (25,624,600,064 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-ZTC-v9",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-ZTC-v9",
            "params": "27B (25,624,600,064 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-35B-ZTC-Vision",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-35B-ZTC-Vision",
            "params": "35B total, about 3B active (MoE; 34,598,622,576 by the Hub's safetensors count)"
          }
        ],
        "olderCount": 19,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "VIDRAFT Inc. (named on vidraft.net); the card's citation names FINAL-Bench and VIDRAFT_LAB",
        "domain": "vidraft.net",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-11-03",
        "notes": [
          "vidraft.net links to the FINAL-Bench organisation on Hugging Face and lists Darwin-36B-Opus by name. Every commit to the repository is by one account, SeaWolf-AI.",
          "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored. The licence is Apache 2.0 in the card's metadata and, since 1 November 2026, in a LICENSE file.",
          "No changelog. Commit titles name the weight versions, v1 to v3 on 22 and 23 April 2026, replaced in the same repository.",
          "vidraft.net/.well-known/security.txt returns 404, so there is no security.txt.",
          "unchecked: the domain's registration date."
        ],
        "score": 44
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/darwin-36b-opus.json",
      "live": {
        "slug": "darwin-36b-opus",
        "securityTxt": {
          "url": "https://vidraft.net/.well-known/security.txt",
          "state": "valid",
          "expires": "2027-11-01T00:00:00.000Z",
          "checkedAt": "2026-11-10T16:09:31.979229229Z"
        },
        "domain": {
          "domain": "vidraft.net",
          "registered": "2025-11-27",
          "source": "https://rdap.verisign.com/net/v1/domain/vidraft.net",
          "checkedAt": "2026-11-08T15:12:31.077394527Z"
        },
        "updatedAt": "2026-11-10T16:09:31.979229229Z"
      }
    },
    "answer": "Darwin-36B-Opus scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category.",
    "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": 20,
        "category": "reach",
        "leads": "darwin-36b-opus",
        "name": "Reach",
        "reasons": {
          "a": "Memory 20, the publisher's Q4_K_M GGUF is 21.2 GB and needs about 25.4 GB with the fifth added, so 32 GB. Runtimes 20, the text-only Qwen3.5 MoE class runs in released vLLM, SGLang, Transformers and llama.cpp, while Ollama's and LM Studio's entries are the base's, not this model's. Builds 15, FINAL-Bench's POCKET-35B-GGUF has it at four precisions. Terms 15, Apache 2.0 with nothing added, with a LICENSE file since 1 November 2026, and Apache 2.0 on the base Qwen3.6-35B-A3B too. Download 10, nothing is gated. Hosted 0, no provider or API serves it.",
          "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": 80,
          "b": 60
        }
      },
      {
        "by": 10,
        "category": "risk",
        "leads": "darwin-36b-opus",
        "name": "Risk",
        "reasons": {
          "a": "File safety 25, safetensors and GGUF only with no code in the repository, so the card's trust_remote_code flag loads nothing extra. Provenance 15, the files are in the FINAL-Bench organisation that vidraft.net links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published. Licence risk 15, Apache 2.0 through the whole chain with no conditions added. Security programme 0, no security.txt, policy or contact.",
          "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": 55,
          "b": 45
        }
      },
      {
        "by": 10,
        "category": "interface",
        "leads": "darwin-36b-opus",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, Qwen3.6's Jinja template in the repository. Tool-calling format 10, the format is only in the template and the card says nothing about tools. Trained tool calling 20, inherited from the base that was trained for it, with several calls in one turn in the template, though the publisher neither claims nor tests it. Structured output 0. Reasoning control 10, the template turns thinking off per request and the card shows where the reasoning comes back. Context 10, 262,144 tokens.",
          "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": "upkeep",
        "leads": "darwin-36b-opus",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 11, it covers architecture, parameters, context and languages but not intended use, limitations or a knowledge cut-off. Training data 5, the reasoning parent's fine-tune is described without datasets or a cut-off. Last change 20, on 1 November 2026 the publisher added a LICENSE file and a corrected eval_results note to the main repository and edited the POCKET-35B-GGUF card, read as this run reads card edits on other open-weight listings (Muse Glimmer 30B, MiMo-V2.6 Distill Qwen 9B, Apertus v1.5 8B). The weights date from 23 April and the GGUF build from 22 July. Responsiveness 20, the publisher answered 8 of the 13 discussions, and two of the rest are its own posts. Version policy 5, a first release whose weights were replaced twice in its first day with commit titles but no card note. File health 0, the card's head counts and base still disagree with the files, and the generation config drops the base's end-of-turn stop token. 11 + 5 + 20 + 20 + 5 + 0 = 61.",
          "b": "Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claimed) are on the card. Training data 15, the training-content summary the card links names the source categories (Common Crawl and other public datasets, commercially licensed data, the Ant Spider crawler, synthetic data), the size band (over 10 trillion text tokens), data collected up to about July 2026 and the filtering, without listing datasets with sizes. Last change 20, the newest commit, on 4 November 2026, edited the card, six days before this check, and the files went up on 27 October. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (both opened on 27 October 2026) has a reply from an inclusionAI member. Version policy 5, the update went into a repository of its own and Ling-3.1-flash and Ling 3.0 stay in theirs. File health 5, the card states a 1M-token context while config.json gives 262,144 with no rope scaling, and its serve commands name the earlier repository as the model path. 11 + 15 + 20 + 0 + 5 + 5 = 56."
        },
        "scores": {
          "a": 61,
          "b": 56
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "FINAL-Bench (VIDRAFT)",
        "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": "Apache-2.0",
        "b": "MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-04-23",
        "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": "2.5/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Darwin-36B-Opus scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category.",
        "question": "Which is better for AI agents, Darwin-36B-Opus or Ling-3.1-flash-1019?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 80 against 60",
          "Risk, 55 against 45",
          "Agent interface, 70 against 60",
          "Documentation and upkeep, 61 against 56"
        ],
        "also": null,
        "goodFor": "Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required",
        "slug": "darwin-36b-opus",
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        "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": 20,
        "darwin-36b-opus": 80,
        "edge": "darwin-36b-opus",
        "key": "reach",
        "ling-3-1-flash-1019": 60,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 10,
        "darwin-36b-opus": 55,
        "edge": "darwin-36b-opus",
        "key": "risk",
        "ling-3-1-flash-1019": 45,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 10,
        "darwin-36b-opus": 70,
        "edge": "darwin-36b-opus",
        "key": "interface",
        "ling-3-1-flash-1019": 60,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 5,
        "darwin-36b-opus": 61,
        "edge": "darwin-36b-opus",
        "key": "upkeep",
        "ling-3-1-flash-1019": 56,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Darwin-36B-Opus scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "darwin-36b-opus": "A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.",
      "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",
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    "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.min.md"
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  "markdown": "Darwin-36B-Opus scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Darwin-36B-Opus: grade C, 61/100, rank #43 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/darwin-36b-opus.md · JSON https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.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### Darwin-36B-Opus (C)\n\nGood for: Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required\n\nAhead on:\n- Reach, 80 against 60\n- Risk, 55 against 45\n- Agent interface, 70 against 60\n- Documentation and upkeep, 61 against 56\n\nWatch for: The merge method is proprietary and the current weights include an undescribed targeted refinement\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\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### Reach: Darwin-36B-Opus +20\n\n- Darwin-36B-Opus (80): Memory 20, the publisher's Q4_K_M GGUF is 21.2 GB and needs about 25.4 GB with the fifth added, so 32 GB. Runtimes 20, the text-only Qwen3.5 MoE class runs in released vLLM, SGLang, Transformers and llama.cpp, while Ollama's and LM Studio's entries are the base's, not this model's. Builds 15, FINAL-Bench's POCKET-35B-GGUF has it at four precisions. Terms 15, Apache 2.0 with nothing added, with a LICENSE file since 1 November 2026, and Apache 2.0 on the base Qwen3.6-35B-A3B too. Download 10, nothing is gated. Hosted 0, no provider or API serves it.\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: Darwin-36B-Opus +10\n\n- Darwin-36B-Opus (55): File safety 25, safetensors and GGUF only with no code in the repository, so the card's trust_remote_code flag loads nothing extra. Provenance 15, the files are in the FINAL-Bench organisation that vidraft.net links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published. Licence risk 15, Apache 2.0 through the whole chain with no conditions added. Security programme 0, no security.txt, policy or contact.\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### Agent interface: Darwin-36B-Opus +10\n\n- Darwin-36B-Opus (70): Chat template 20, Qwen3.6's Jinja template in the repository. Tool-calling format 10, the format is only in the template and the card says nothing about tools. Trained tool calling 20, inherited from the base that was trained for it, with several calls in one turn in the template, though the publisher neither claims nor tests it. Structured output 0. Reasoning control 10, the template turns thinking off per request and the card shows where the reasoning comes back. Context 10, 262,144 tokens.\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### Documentation and upkeep: Darwin-36B-Opus +5\n\n- Darwin-36B-Opus (61): Model card 11, it covers architecture, parameters, context and languages but not intended use, limitations or a knowledge cut-off. Training data 5, the reasoning parent's fine-tune is described without datasets or a cut-off. Last change 20, on 1 November 2026 the publisher added a LICENSE file and a corrected eval_results note to the main repository and edited the POCKET-35B-GGUF card, read as this run reads card edits on other open-weight listings (Muse Glimmer 30B, MiMo-V2.6 Distill Qwen 9B, Apertus v1.5 8B). The weights date from 23 April and the GGUF build from 22 July. Responsiveness 20, the publisher answered 8 of the 13 discussions, and two of the rest are its own posts. Version policy 5, a first release whose weights were replaced twice in its first day with commit titles but no card note. File health 0, the card's head counts and base still disagree with the files, and the generation config drops the base's end-of-turn stop token. 11 + 5 + 20 + 20 + 5 + 0 = 61.\n- Ling-3.1-flash-1019 (56): Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claimed) are on the card. Training data 15, the training-content summary the card links names the source categories (Common Crawl and other public datasets, commercially licensed data, the Ant Spider crawler, synthetic data), the size band (over 10 trillion text tokens), data collected up to about July 2026 and the filtering, without listing datasets with sizes. Last change 20, the newest commit, on 4 November 2026, edited the card, six days before this check, and the files went up on 27 October. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (both opened on 27 October 2026) has a reply from an inclusionAI member. Version policy 5, the update went into a repository of its own and Ling-3.1-flash and Ling 3.0 stay in theirs. File health 5, the card states a 1M-token context while config.json gives 262,144 with no rope scaling, and its serve commands name the earlier repository as the model path. 11 + 15 + 20 + 0 + 5 + 5 = 56.\n\n## Score by category\n\n| Category | Weight | Darwin-36B-Opus | Ling-3.1-flash-1019 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 80 | 60 | Darwin-36B-Opus +20 |\n| Risk | 20% (20 this run) | 55 | 45 | Darwin-36B-Opus +10 |\n| Agent interface | 10% (10 this run) | 70 | 60 | Darwin-36B-Opus +10 |\n| Documentation and upkeep | 10% (10 this run) | 61 | 56 | Darwin-36B-Opus +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **54.8 · C** | |\n\n## Facts side by side\n\n| Fact | Darwin-36B-Opus | Ling-3.1-flash-1019 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | FINAL-Bench (VIDRAFT) | 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 | Apache-2.0 | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-04-23 | 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 | 2.5/5 (4) | none |\n\n## How the scores have moved\n\n### Darwin-36B-Opus\n\n- no change on 3 November 2026: correction\n\n### Ling-3.1-flash-1019\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Darwin-36B-Opus.** A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.\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### Darwin-36B-Opus\n\n1. Quickest start is `llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja`, about 21 GB of files\n2. On the reference machine BF16 fits, `vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parsers for Qwen3.6's format\n3. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention\n4. The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces\n5. generation_config.json stops only on the end-of-text token, so add `\u003c|im_end|\u003e` as a stop token if a runtime keeps generating after the turn ends\n6. Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files\n7. Validate JSON output yourself, since structured output isn't documented\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, Darwin-36B-Opus or Ling-3.1-flash-1019?\n\nDarwin-36B-Opus scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-1-flash-1019.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"darwin-36b-opus\", \"b\": \"ling-3-1-flash-1019\"}`. From a terminal: `anchor compare darwin-36b-opus ling-3-1-flash-1019`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json\n\n## Other comparisons with Darwin-36B-Opus or Ling-3.1-flash-1019\n\n- [Agents-A1-4B vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/agents-a1-4b-vs-darwin-36b-opus.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 Darwin-36B-Opus](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-darwin-36b-opus.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 Darwin-36B-Opus](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-darwin-36b-opus.md)\n- [Apodex-1.1-mini vs 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