{
  "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 LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and agent interface.",
    "b": {
      "slug": "longcat-2-5",
      "name": "LongCat-2.5",
      "vendor": "Meituan (LongCat)",
      "vendorUrl": "https://longcat.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "LongCat-2.5 is Meituan's open-weight flagship, a multimodal mixture-of-experts model of 1.6T parameters with about 48B active per token, built for long agentic coding work. MIT licence. The weights are 3,562 GB, and the card documents deployment on NPU hardware only.",
      "url": "https://www.anchorterminal.com/tools/longcat-2-5",
      "markdownUrl": "https://www.anchorterminal.com/tools/longcat-2-5.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/longcat-2-5.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/longcat-2-5.json",
      "dns": "longcat-2-5.grade.anchorterminal.com",
      "repo": "https://huggingface.co/meituan-longcat/LongCat-2.5",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "meituan-longcat/LongCat-2.5"
        },
        {
          "registry": "huggingface",
          "name": "meituan-longcat/LongCat-2.5-W4A4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under the MIT licence. Running it yourself is a data-centre job: 3,562 GB in BF16, or 1,336 GB for Meituan's 4-bit build, which the card says is for INT4 computation on NPU accelerators (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/meituan-longcat/LongCat-2.5",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "agentic-coding",
        "mit",
        "safetensors",
        "int4",
        "npu",
        "self-hosted"
      ],
      "lastRelease": "2026-11-10",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 50.5,
        "grade": "D",
        "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": 107,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 75,
          "reach": 35,
          "risk": 60,
          "upkeep": 46
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "Meituan's flagship is MIT-licensed and documented for tool calling and switchable reasoning, with strong numbers of its own on agentic coding. Almost nobody can run it: 3,562 GB of weights, a 1,336 GB 4-bit build for NPU accelerators, and no released runtime with its architecture. A model to watch until a runtime or a provider picks it up.",
        "bestFor": "Operators with NPU clusters, and anyone tracking what the open flagships can do",
        "strengths": [
          "MIT licence, ungated",
          "Tool calling documented with a worked example",
          "Reasoning can be switched per request and comes back as reasoning_content",
          "Meituan publishes its own 4-bit build",
          "Updated on the day we checked"
        ],
        "weaknesses": [
          "3,562 GB in BF16 and 1,336 GB at 4 bits",
          "No released runtime has its architecture",
          "The only documented deployment is on NPU hardware through Meituan's fork",
          "config.json names model code that isn't in the repository",
          "No stated context length, languages, safety results or data sources",
          "No inference provider serves it"
        ],
        "agentNotes": [
          "You can't run this on a workstation or a single GPU server. Plan for a provider, and none serves it yet",
          "If an operator serves it, call it as an OpenAI-compatible chat API with tools in the function format",
          "Pass `chat_template_kwargs` with `enable_thinking` true or false",
          "With thinking on, keep earlier reasoning in the history (`save_history_reasoning_content` true), as the card recommends",
          "The card's results use temperature 1.0 and top_p 0.95",
          "Its benchmark table is Meituan's own. The unmarked scores are in-house"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "D",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 50.5
          }
        ],
        "editorialScores": {
          "interface": 75,
          "reach": 35,
          "risk": 60,
          "upkeep": 46
        },
        "provenanceScore": 49,
        "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": "# No released runtime loads it. Meituan's NPU instructions are in its SGLang fork:\n# github.com/meituan-longcat/SGLang-FluentLLM, branch longcat-2.5-npu, npu_test/ReadMe.md",
        "http": "# The card's example calls an OpenAI-compatible chat completions API with tools, and passes\n# extra_body={\"chat_template_kwargs\": {\"enable_thinking\": true, \"save_history_reasoning_content\": true}}"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/longcat-2-5"
      },
      "weights": {
        "trainedBy": "Meituan (LongCat team)",
        "builtOn": "LongCat-2.0 and LongCat-Next, per the card",
        "params": "1.6T",
        "active": "48B",
        "context": 524288,
        "goodFor": "Long agentic coding and research runs with images, for an operator with NPU clusters. Nobody else can run it yet.",
        "runtimes": [],
        "builds": [
          {
            "name": "LongCat-2.5-W4A4",
            "url": "https://huggingface.co/meituan-longcat/LongCat-2.5-W4A4",
            "who": "publisher",
            "precision": "int4",
            "sizeGB": 1336,
            "memoryGB": 2048,
            "format": "safetensors",
            "note": "Meituan's 4-bit build of the experts' weights and activations, for INT4 computation on NPU accelerators"
          },
          {
            "name": "LongCat-2.5 (BF16 safetensors)",
            "url": "https://huggingface.co/meituan-longcat/LongCat-2.5",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 3562,
            "memoryGB": 8192,
            "format": "safetensors",
            "note": "210 files"
          }
        ],
        "run": "See github.com/meituan-longcat/SGLang-FluentLLM, branch longcat-2.5-npu",
        "runBuild": "LongCat-2.5-W4A4",
        "checked": "2026-11-10",
        "minMemoryGB": 2048
      },
      "family": {
        "lab": "Meituan (LongCat)",
        "family": "LongCat-2",
        "url": "https://www.anchorterminal.com/open-weights/#meituan-longcat",
        "others": [
          {
            "name": "LongCat-2.5-W4A4",
            "url": "https://huggingface.co/meituan-longcat/LongCat-2.5-W4A4"
          },
          {
            "name": "LongCat-2.0",
            "url": "https://huggingface.co/meituan-longcat/LongCat-2.0"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Meituan, named in the card's licence section. The legal entity wasn't looked up",
        "domain": "longcat.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "https://huggingface.co/meituan-longcat/LongCat-2.5/blob/main/LICENSE",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/meituan-longcat/LongCat-2.5/commits/main",
        "securityTxt": "unknown",
        "checked": "2026-11-10",
        "notes": [
          "longcat.ai has no robots.txt (the request returns a not-found message) and its pages are JavaScript applications that gave no text on 10 November 2026, so the site's own statements weren't read.",
          "The domain's registration date wasn't looked up.",
          "Nothing is hosted under this listing, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the commit history, 50 commits or more since 4 November 2026."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/longcat-2-5.json"
    },
    "edges": [
      {
        "by": 45,
        "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, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB. The BF16 files are 3,562 GB. Runtimes 0, none of the six runs it in a released version: vLLM 0.33.0, SGLang 0.5.23, Transformers 5.22.2 and llama.cpp b12242 have no LongcatCausalLM or pro_v code, and the model code config.json names isn't in the repository. Builds 10, one quantised build from Meituan, the W4A4 repository (4-bit experts, 1,336 GB). Terms 15, MIT in the metadata, the LICENSE file and the card, with nothing added. Download 10, the Hub API reports gated false for both repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 0 + 0 + 10 + 15 + 10 + 0 = 35."
        },
        "scores": {
          "a": 80,
          "b": 35
        }
      },
      {
        "by": 15,
        "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, limitations (the usage considerations), the architecture and the parameter counts are on the card. Training data 5, A general description of the training stages and where the reinforcement learning tasks came from, with no sources, sizes or cut-off. Last change 20, the last commit, on 10 November 2026, updated the card, on the day of this check. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (9 and 10 November 2026) has a reply from a meituan-longcat member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, LongCat-2.0 stays in its own repositories and 2.5 came out in new ones, with no dated note on the older ones that we read. File health 5, the template is in both places and agrees, but config.json's auto_map names configuration_longcat_oe and modeling_longcat_oe, which aren't in the repository, and the tokenizer config's 131,072-token length is a quarter of the config's 524,288 positions. 11 + 5 + 20 + 0 + 5 + 5 = 46."
        },
        "scores": {
          "a": 61,
          "b": 46
        }
      },
      {
        "by": 5,
        "category": "risk",
        "leads": "longcat-2-5",
        "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 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the meituan-longcat organisation, the name of Meituan's GitHub organisation that the card links for deployment, and the card's licence names Meituan (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions under Usage Considerations: not evaluated for every use, assess accuracy, safety and fairness before sensitive use, and follow the law. Licence risk 15, MIT with no use policy, no threshold and no right to change the terms. Security programme 0, no way to report a flaw on the card beyond a general contact, and Meituan's own security pages weren't looked up, so this scores as absent and is an open question. 25 + 15 + 0 + 5 + 15 + 0 = 60."
        },
        "scores": {
          "a": 55,
          "b": 60
        }
      },
      {
        "by": 5,
        "category": "interface",
        "leads": "longcat-2-5",
        "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 (11,823 characters), with a copy in tokenizer_config.json. Tool-calling format 25, the card documents how tools are declared (the OpenAI function format) and how calls come back (tool_calls with an id, a name and JSON arguments, answered by a tool message), in a worked example against an OpenAI-compatible server. Trained tool calling 10, the card describes reinforcement learning on long agentic tasks and shows one tool call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, enable_thinking on or off per request through chat_template_kwargs, with the reasoning returned as reasoning_content, both shown on the card. Context 10, the card states no context length, but config.json gives 524,288 positions and the card's own evaluations ran at 512K and 1M sequence lengths after what it calls long-context training, so 128K or more is taken as trained. 20 + 25 + 10 + 0 + 10 + 10 = 75."
        },
        "scores": {
          "a": 70,
          "b": 75
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "FINAL-Bench (VIDRAFT)",
        "b": "Meituan (LongCat)",
        "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": "2026-11-10",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "not read yet",
        "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 LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and agent interface.",
        "question": "Which is better for AI agents, Darwin-36B-Opus or LongCat-2.5?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 80 against 35",
          "Documentation and upkeep, 61 against 46"
        ],
        "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",
        "watchFor": "The merge method is proprietary and the current weights include an undescribed targeted refinement"
      },
      {
        "aheadOn": [
          "Risk, 60 against 55",
          "Agent interface, 75 against 70"
        ],
        "also": null,
        "goodFor": "Operators with NPU clusters, and anyone tracking what the open flagships can do",
        "slug": "longcat-2-5",
        "watchFor": "3,562 GB in BF16 and 1,336 GB at 4 bits"
      }
    ],
    "history": {
      "darwin-36b-opus": [
        {
          "causes": [
            "correction"
          ],
          "date": "2026-11-03",
          "delta": 0,
          "from": 61,
          "fromGrade": "C",
          "to": 61,
          "toGrade": "C"
        }
      ],
      "longcat-2-5": null
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-darwin-36b-opus.json",
        "title": "Agents-A1-4B vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-longcat-2-5.json",
        "title": "Agents-A1-4B vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-darwin-36b-opus.json",
        "title": "Apertus v1.5 8B vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-longcat-2-5.json",
        "title": "Apertus v1.5 8B vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-darwin-36b-opus.json",
        "title": "Apodex-1.1-mini vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-longcat-2-5.json",
        "title": "Apodex-1.1-mini vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-darwin-36b-opus.json",
        "title": "Arete-27B vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-longcat-2-5.json",
        "title": "Arete-27B vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus.json",
        "title": "BigBang-v1 vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-longcat-2-5.json",
        "title": "BigBang-v1 vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus.json",
        "title": "Carbon-X vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-longcat-2-5.json",
        "title": "Carbon-X vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-darwin-36b-opus.json",
        "title": "Cola2 vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-darwin-36b-opus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-longcat-2-5.json",
        "title": "Cola2 vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-longcat-2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus.json",
        "title": "Cosmos-Reason2-2B vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus"
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        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-o-4-5.json",
        "title": "LongCat-2.5 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-v-4-7-1b.json",
        "title": "LongCat-2.5 vs MiniCPM-V 4.7 1B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-v-4-7-1b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "LongCat-2.5 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm5-2b.json",
        "title": "LongCat-2.5 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m2-5.json",
        "title": "LongCat-2.5 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m2-7.json",
        "title": "LongCat-2.5 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m3-1-flash.json",
        "title": "LongCat-2.5 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-minimax-m3-1-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-mistral-large-4.json",
        "title": "LongCat-2.5 vs Mistral Large 4",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-mistral-large-4"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-muse-glimmer-30b.json",
        "title": "LongCat-2.5 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nanbeige-4-2-3b.json",
        "title": "LongCat-2.5 vs Nanbeige4.2-3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nanbeige-4-2-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nanbeige-4-3-33b.json",
        "title": "LongCat-2.5 vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nanbeige-4-3-33b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-5-bolt-e4b-4gb.json",
        "title": "LongCat-2.5 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-5-bolt-e4b-4gb"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "LongCat-2.5 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-30b-a3b.json",
        "title": "LongCat-2.5 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-4b.json",
        "title": "LongCat-2.5 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "LongCat-2.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-super-120b-a12b.json",
        "title": "LongCat-2.5 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "LongCat-2.5 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-north-mini-code-1-0.json",
        "title": "LongCat-2.5 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0.json",
        "title": "LongCat-2.5 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-olmo-3-7b-think.json",
        "title": "LongCat-2.5 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-122b.json",
        "title": "LongCat-2.5 vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-35b-a3b.json",
        "title": "LongCat-2.5 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-397b.json",
        "title": "LongCat-2.5 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-9b.json",
        "title": "LongCat-2.5 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-otel-2-0-llm-31b-it.json",
        "title": "LongCat-2.5 vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b.json",
        "title": "LongCat-2.5 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "LongCat-2.5 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-4b-instruct-2507.json",
        "title": "LongCat-2.5 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-0-8b.json",
        "title": "LongCat-2.5 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-122b-a10b.json",
        "title": "LongCat-2.5 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-2b.json",
        "title": "LongCat-2.5 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-397b-a17b.json",
        "title": "LongCat-2.5 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-4b.json",
        "title": "LongCat-2.5 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-9b.json",
        "title": "LongCat-2.5 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-6-27b.json",
        "title": "LongCat-2.5 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-6-35b-a3b.json",
        "title": "LongCat-2.5 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-8-27b.json",
        "title": "LongCat-2.5 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-8-flash-next.json",
        "title": "LongCat-2.5 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-coder-next.json",
        "title": "LongCat-2.5 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-2b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-32b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-4b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-8b-instruct.json",
        "title": "LongCat-2.5 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwopus3-8-27b-flash-v2.json",
        "title": "LongCat-2.5 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-recursive-flint.json",
        "title": "LongCat-2.5 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ripple-65b-preview.json",
        "title": "LongCat-2.5 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-sensenova-loop-9b-preview.json",
        "title": "LongCat-2.5 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-smollm3-3b.json",
        "title": "LongCat-2.5 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-spark-x2-6-4b.json",
        "title": "LongCat-2.5 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-step-3-7-flash.json",
        "title": "LongCat-2.5 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-swift-1-5-qwen3-8-27b.json",
        "title": "LongCat-2.5 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "LongCat-2.5 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-thinkingcap-qwen3-8-27b.json",
        "title": "LongCat-2.5 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-unlimited-ocr-2.json",
        "title": "LongCat-2.5 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-wevisone-vl-2b.json",
        "title": "LongCat-2.5 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-wevisone-vl-4b.json",
        "title": "LongCat-2.5 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-zaya1-8b.json",
        "title": "LongCat-2.5 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 45,
        "darwin-36b-opus": 80,
        "edge": "darwin-36b-opus",
        "key": "reach",
        "longcat-2-5": 35,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 5,
        "darwin-36b-opus": 55,
        "edge": "longcat-2-5",
        "key": "risk",
        "longcat-2-5": 60,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 5,
        "darwin-36b-opus": 70,
        "edge": "longcat-2-5",
        "key": "interface",
        "longcat-2-5": 75,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 15,
        "darwin-36b-opus": 61,
        "edge": "darwin-36b-opus",
        "key": "upkeep",
        "longcat-2-5": 46,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Darwin-36B-Opus scores 61 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and agent interface. 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.",
      "longcat-2-5": "Meituan's flagship is MIT-licensed and documented for tool calling and switchable reasoning, with strong numbers of its own on agentic coding. Almost nobody can run it: 3,562 GB of weights, a 1,336 GB 4-bit build for NPU accelerators, and no released runtime with its architecture. A model to watch until a runtime or a provider picks it up."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5",
    "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5.min.md"
  },
  "markdown": "Darwin-36B-Opus scores 61 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and agent interface. 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- LongCat-2.5: grade D, 50.5/100, rank #145 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/longcat-2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/longcat-2-5.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 35\n- Documentation and upkeep, 61 against 46\n\nWatch for: The merge method is proprietary and the current weights include an undescribed targeted refinement\n\n### LongCat-2.5 (D)\n\nGood for: Operators with NPU clusters, and anyone tracking what the open flagships can do\n\nAhead on:\n- Risk, 60 against 55\n- Agent interface, 75 against 70\n\nWatch for: 3,562 GB in BF16 and 1,336 GB at 4 bits\n\n\n## Why the edge\n\n### Reach: Darwin-36B-Opus +45\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- LongCat-2.5 (35): Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB. The BF16 files are 3,562 GB. Runtimes 0, none of the six runs it in a released version: vLLM 0.33.0, SGLang 0.5.23, Transformers 5.22.2 and llama.cpp b12242 have no LongcatCausalLM or pro_v code, and the model code config.json names isn't in the repository. Builds 10, one quantised build from Meituan, the W4A4 repository (4-bit experts, 1,336 GB). Terms 15, MIT in the metadata, the LICENSE file and the card, with nothing added. Download 10, the Hub API reports gated false for both repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 0 + 0 + 10 + 15 + 10 + 0 = 35.\n\n### Documentation and upkeep: Darwin-36B-Opus +15\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- LongCat-2.5 (46): Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card. Training data 5, A general description of the training stages and where the reinforcement learning tasks came from, with no sources, sizes or cut-off. Last change 20, the last commit, on 10 November 2026, updated the card, on the day of this check. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (9 and 10 November 2026) has a reply from a meituan-longcat member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, LongCat-2.0 stays in its own repositories and 2.5 came out in new ones, with no dated note on the older ones that we read. File health 5, the template is in both places and agrees, but config.json's auto_map names configuration_longcat_oe and modeling_longcat_oe, which aren't in the repository, and the tokenizer config's 131,072-token length is a quarter of the config's 524,288 positions. 11 + 5 + 20 + 0 + 5 + 5 = 46.\n\n### Risk: LongCat-2.5 +5\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- LongCat-2.5 (60): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the meituan-longcat organisation, the name of Meituan's GitHub organisation that the card links for deployment, and the card's licence names Meituan (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions under Usage Considerations: not evaluated for every use, assess accuracy, safety and fairness before sensitive use, and follow the law. Licence risk 15, MIT with no use policy, no threshold and no right to change the terms. Security programme 0, no way to report a flaw on the card beyond a general contact, and Meituan's own security pages weren't looked up, so this scores as absent and is an open question. 25 + 15 + 0 + 5 + 15 + 0 = 60.\n\n### Agent interface: LongCat-2.5 +5\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- LongCat-2.5 (75): Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json. Tool-calling format 25, the card documents how tools are declared (the OpenAI function format) and how calls come back (tool_calls with an id, a name and JSON arguments, answered by a tool message), in a worked example against an OpenAI-compatible server. Trained tool calling 10, the card describes reinforcement learning on long agentic tasks and shows one tool call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, enable_thinking on or off per request through chat_template_kwargs, with the reasoning returned as reasoning_content, both shown on the card. Context 10, the card states no context length, but config.json gives 524,288 positions and the card's own evaluations ran at 512K and 1M sequence lengths after what it calls long-context training, so 128K or more is taken as trained. 20 + 25 + 10 + 0 + 10 + 10 = 75.\n\n## Score by category\n\n| Category | Weight | Darwin-36B-Opus | LongCat-2.5 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 80 | 35 | Darwin-36B-Opus +45 |\n| Risk | 20% (20 this run) | 55 | 60 | LongCat-2.5 +5 |\n| Agent interface | 10% (10 this run) | 70 | 75 | LongCat-2.5 +5 |\n| Documentation and upkeep | 10% (10 this run) | 61 | 46 | Darwin-36B-Opus +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **50.5 · D** | |\n\n## Facts side by side\n\n| Fact | Darwin-36B-Opus | LongCat-2.5 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | FINAL-Bench (VIDRAFT) | Meituan (LongCat) |\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 | 2026-11-10 |\n| Terms last updated | no document linked | not read yet |\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### LongCat-2.5\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**LongCat-2.5.** Meituan's flagship is MIT-licensed and documented for tool calling and switchable reasoning, with strong numbers of its own on agentic coding. Almost nobody can run it: 3,562 GB of weights, a 1,336 GB 4-bit build for NPU accelerators, and no released runtime with its architecture. A model to watch until a runtime or a provider picks it up.\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### LongCat-2.5\n\n1. You can't run this on a workstation or a single GPU server. Plan for a provider, and none serves it yet\n2. If an operator serves it, call it as an OpenAI-compatible chat API with tools in the function format\n3. Pass `chat_template_kwargs` with `enable_thinking` true or false\n4. With thinking on, keep earlier reasoning in the history (`save_history_reasoning_content` true), as the card recommends\n5. The card's results use temperature 1.0 and top_p 0.95\n6. Its benchmark table is Meituan's own. The unmarked scores are in-house\n\n## Questions\n\n### Which is better for AI agents, Darwin-36B-Opus or LongCat-2.5?\n\nDarwin-36B-Opus scores 61 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 2 of 4 scored categories. LongCat-2.5 leads on risk and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-longcat-2-5.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"darwin-36b-opus\", \"b\": \"longcat-2-5\"}`. From a terminal: `anchor compare darwin-36b-opus longcat-2-5`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/longcat-2-5.json\n\n## Other comparisons with Darwin-36B-Opus or LongCat-2.5\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 LongCat-2.5](https://www.anchorterminal.com/compare/agents-a1-4b-vs-longcat-2-5.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 LongCat-2.5](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-longcat-2-5.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 LongCat-2.5](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-longcat-2-5.md)\n- [Arete-27B vs 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