{
  "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 and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C).",
    "b": {
      "slug": "lfm3-omni-2b",
      "name": "LFM3-Omni-2B",
      "vendor": "Liquid AI",
      "vendorUrl": "https://www.liquid.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "LFM3-Omni-2B is Liquid AI's open-weight 2.17B omni model for on-device use, taking text, images, video and audio and answering in text or speech, with tool calling and a 32K-token context, released on 27 October 2026 with GGUF and MLX builds.",
      "url": "https://www.anchorterminal.com/tools/lfm3-omni-2b",
      "markdownUrl": "https://www.anchorterminal.com/tools/lfm3-omni-2b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lfm3-omni-2b.json",
      "dns": "lfm3-omni-2b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/LiquidAI/LFM3-Omni-2B",
      "license": "LFM Open License v1.0 (free commercial use below $10M annual revenue)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Omni-2B"
        },
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Omni-2B-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Omni-2B-MLX-4bit"
        },
        {
          "registry": "ollama",
          "name": "lfm3-omni"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and Liquid's GGUF, MLX and ONNX repositories are not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under the LFM Open License v1.0, commercial use included for organisations with under $10M in annual revenue; above that, commercial use isn't licensed. Running it yourself costs little hardware, 1.10 GB for Liquid's Q4_K_M GGUF with its 0.29 GB projector file and 4.49 GB in BF16. Liquid's API also serves it, at prices shown in its console (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://docs.liquid.ai/lfm/models/lfm3-omni-2b",
      "llmsTxt": "https://docs.liquid.ai/llms.txt",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "omni",
        "vision",
        "video",
        "audio",
        "speech",
        "small",
        "edge",
        "tool-calling",
        "custom-licence",
        "safetensors",
        "gguf",
        "mlx",
        "onnx",
        "self-hosted"
      ],
      "lastRelease": "2026-11-03",
      "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": 57,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 80,
          "risk": 40,
          "upkeep": 49
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "One 2.17B model that sees, listens and talks on an 8 GB machine and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, it doesn't reason, Liquid hasn't answered a question on the repository, and there are no safety results or data sources.",
        "bestFor": "Voice and camera agents on a laptop or phone that want one small model for hearing, seeing, speaking and calling tools",
        "strengths": [
          "One model for text, images, video, audio and speech on an 8 GB machine",
          "Speech output and a realtime speech server in released llama.cpp",
          "Tool calls from spoken requests, in a documented format",
          "Updated a week before this check",
          "Liquid's own API serves it"
        ],
        "weaknesses": [
          "Only llama.cpp and Ollama run it in a release",
          "A 32K-token context, which video and audio fill quickly",
          "It doesn't reason, and structured output isn't documented",
          "None of 12 questions on the repository has a reply from Liquid",
          "Loading in Transformers runs 14 Python files from the repository",
          "No safety results, security contact or training data description"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf LiquidAI/LFM3-Omni-2B-GGUF:Q4_K_M --jinja` or `ollama run lfm3-omni`",
          "Greedy decoding for text. For speech use audio_temperature 0.4 and audio_repetition_penalty 1.2, per the card",
          "The context is 32K, and llama.cpp samples video at 2 frames a second up to 384 frames",
          "Parse tool calls yourself from the XML it returns",
          "It doesn't reason, so don't pass enable_thinking",
          "Validate JSON output yourself"
        ],
        "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": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 80,
          "risk": 40,
          "upkeep": 49
        },
        "provenanceScore": 73,
        "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": "llama-server -hf LiquidAI/LFM3-Omni-2B-GGUF:Q4_K_M --jinja\n# or\nollama run lfm3-omni",
        "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/lfm3-omni-2b"
      },
      "sameCompany": [
        "liquid-d1",
        "lfm2-5-2-6b",
        "lfm3-1-7b",
        "lfm3-audio-2b",
        "lfm3-vl-2b"
      ],
      "weights": {
        "trainedBy": "Liquid AI",
        "builtOn": "The LFM3 backbone (Liquid's own; the metadata names no base model)",
        "params": "2.17B",
        "context": 32000,
        "goodFor": "One small on-device model in place of separate speech recognition, vision, language and speech models, for voice chat, questions about video with its soundtrack and tool calls from spoken requests. It doesn't reason.",
        "runtimes": [
          "llama.cpp",
          "Ollama"
        ],
        "builds": [
          {
            "name": "LFM3-Omni-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 4.49,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "Transformers"
            ],
            "note": "Loads in Transformers with the repository's own code. Liquid also publishes an ONNX repository. It has no FP8 or NVFP4 build of this model"
          },
          {
            "name": "LFM3-Omni-2B-GGUF Q8_0",
            "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B-GGUF",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 2.36,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "LFM3-Omni-2B-Q8_0.gguf (1.85 GB) plus mmproj-LFM3-Omni-2B-Q8_0.gguf (0.51 GB)"
          },
          {
            "name": "LFM3-Omni-2B-GGUF Q4_K_M",
            "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.39,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "LFM3-Omni-2B-Q4_K_M.gguf (1.10 GB) plus Liquid's projector file mmproj-LFM3-Omni-2B-Q4_K_M.gguf (0.29 GB), from the Hub's file list. The repository also holds Q4_0, Q8_0, F16 and BF16 files"
          },
          {
            "name": "LFM3-Omni-2B-MLX-4bit",
            "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B-MLX-4bit",
            "who": "publisher",
            "precision": "4bit",
            "sizeGB": 2.11,
            "memoryGB": 8,
            "format": "mlx",
            "runsOn": [
              "MLX-VLM"
            ],
            "note": "Liquid also publishes 8-bit and BF16 MLX builds"
          },
          {
            "name": "ollama lfm3-omni",
            "url": "https://ollama.com/library/lfm3-omni",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 2,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Ollama's library build, size as its tags page shows it on 10 November 2026. The library also has q8_0, bf16, mxfp8 and nvfp4 tags"
          }
        ],
        "run": "llama-server -hf LiquidAI/LFM3-Omni-2B-GGUF:Q4_K_M --jinja",
        "runBuild": "LFM3-Omni-2B-GGUF Q4_K_M",
        "checked": "2026-11-10",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Liquid AI",
        "family": "LFM3",
        "url": "https://www.anchorterminal.com/open-weights/#liquid",
        "others": [
          {
            "name": "LFM3-1.7B-Base",
            "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-Base",
            "params": "1.73B"
          },
          {
            "name": "LFM3-1.7B",
            "url": "https://huggingface.co/LiquidAI/LFM3-1.7B",
            "params": "1.73B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-1-7b"
          },
          {
            "name": "LFM3-VL-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-VL-2B",
            "params": "1.92B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-vl-2b"
          },
          {
            "name": "LFM3-Audio-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B",
            "params": "2.00B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-audio-2b"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Liquid AI, Inc. (the licensor named in the LFM Open License)",
        "domain": "liquid.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/LiquidAI/LFM3-Omni-2B/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "The licence names Liquid AI, Inc. as licensor. The domain's registration date is as recorded on the liquid-d1 listing on 8 October 2026",
          "www.liquid.ai/.well-known/security.txt answered 404 on 10 November 2026"
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/lfm3-omni-2b.json"
    },
    "edges": [
      {
        "by": 15,
        "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). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40."
        },
        "scores": {
          "a": 55,
          "b": 40
        }
      },
      {
        "by": 12,
        "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 14, Intended use (one on-device model in place of separate speech recognition, vision, language and speech models), architecture, parameters (2.17B), context (32K) and the text and speech languages. Training data 5, the card has no training section. Last change 20, the last commit, on 3 November 2026, changed the card's navigation icons, seven days before this check, and the one before it, on 28 October, documented video frame rate and frame limits. Responsiveness 0, none of the 12 discussions that aren't pull requests (27 October to 9 November 2026) has a reply from a LiquidAI member. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 5, the card gives a 32K context while config.json gives the language model 128,000 positions and Liquid's API lists 128,000 for the hosted model, so the card and the files don't agree on context. 14 + 5 + 20 + 0 + 5 + 5 = 49."
        },
        "scores": {
          "a": 61,
          "b": 49
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "FINAL-Bench (VIDRAFT)",
        "b": "Liquid AI",
        "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": "LFM Open License v1.0 (free commercial use below $10M annual revenue)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-04-23",
        "b": "2026-11-03",
        "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 and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C).",
        "question": "Which is better for AI agents, Darwin-36B-Opus or LFM3-Omni-2B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 55 against 40",
          "Documentation and upkeep, 61 against 49"
        ],
        "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": null,
        "also": null,
        "goodFor": "Voice and camera agents on a laptop or phone that want one small model for hearing, seeing, speaking and calling tools",
        "slug": "lfm3-omni-2b",
        "watchFor": "Only llama.cpp and Ollama run it in a release"
      }
    ],
    "history": {
      "darwin-36b-opus": [
        {
          "causes": [
            "correction"
          ],
          "date": "2026-11-03",
          "delta": 0,
          "from": 61,
          "fromGrade": "C",
          "to": 61,
          "toGrade": "C"
        }
      ],
      "lfm3-omni-2b": 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-lfm3-omni-2b.json",
        "title": "Agents-A1-4B vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-omni-2b"
      },
      {
        "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-lfm3-omni-2b.json",
        "title": "Apertus v1.5 8B vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-omni-2b"
      },
      {
        "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-lfm3-omni-2b.json",
        "title": "Apodex-1.1-mini vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-omni-2b"
      },
      {
        "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-lfm3-omni-2b.json",
        "title": "Arete-27B vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-omni-2b"
      },
      {
        "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-lfm3-omni-2b.json",
        "title": "BigBang-v1 vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-omni-2b"
      },
      {
        "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-lfm3-omni-2b.json",
        "title": "Carbon-X vs LFM3-Omni-2B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-omni-2b"
      },
      {
        "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"
      },
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        "json": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-omni-2b.json",
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        "by": 0,
        "darwin-36b-opus": 70,
        "edge": "",
        "key": "interface",
        "lfm3-omni-2b": 70,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 12,
        "darwin-36b-opus": 61,
        "edge": "darwin-36b-opus",
        "key": "upkeep",
        "lfm3-omni-2b": 49,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Darwin-36B-Opus and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). 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.",
      "lfm3-omni-2b": "One 2.17B model that sees, listens and talks on an 8 GB machine and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, it doesn't reason, Liquid hasn't answered a question on the repository, and there are no safety results or data sources."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b",
    "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b.min.md"
  },
  "markdown": "Darwin-36B-Opus and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). 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- LFM3-Omni-2B: grade C, 61/100, rank #71 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/lfm3-omni-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/lfm3-omni-2b.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- Risk, 55 against 40\n- Documentation and upkeep, 61 against 49\n\nWatch for: The merge method is proprietary and the current weights include an undescribed targeted refinement\n\n### LFM3-Omni-2B (C)\n\nGood for: Voice and camera agents on a laptop or phone that want one small model for hearing, seeing, speaking and calling tools\n\nWatch for: Only llama.cpp and Ollama run it in a release\n\n\n## Why the edge\n\n### Risk: Darwin-36B-Opus +15\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- LFM3-Omni-2B (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.\n\n### Documentation and upkeep: Darwin-36B-Opus +12\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- LFM3-Omni-2B (49): Model card 14, Intended use (one on-device model in place of separate speech recognition, vision, language and speech models), architecture, parameters (2.17B), context (32K) and the text and speech languages. Training data 5, the card has no training section. Last change 20, the last commit, on 3 November 2026, changed the card's navigation icons, seven days before this check, and the one before it, on 28 October, documented video frame rate and frame limits. Responsiveness 0, none of the 12 discussions that aren't pull requests (27 October to 9 November 2026) has a reply from a LiquidAI member. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 5, the card gives a 32K context while config.json gives the language model 128,000 positions and Liquid's API lists 128,000 for the hosted model, so the card and the files don't agree on context. 14 + 5 + 20 + 0 + 5 + 5 = 49.\n\n## Score by category\n\n| Category | Weight | Darwin-36B-Opus | LFM3-Omni-2B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 80 | 80 | even |\n| Risk | 20% (20 this run) | 55 | 40 | Darwin-36B-Opus +15 |\n| Agent interface | 10% (10 this run) | 70 | 70 | even |\n| Documentation and upkeep | 10% (10 this run) | 61 | 49 | Darwin-36B-Opus +12 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Darwin-36B-Opus | LFM3-Omni-2B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | FINAL-Bench (VIDRAFT) | Liquid AI |\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 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-04-23 | 2026-11-03 |\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### LFM3-Omni-2B\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**LFM3-Omni-2B.** One 2.17B model that sees, listens and talks on an 8 GB machine and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, it doesn't reason, Liquid hasn't answered a question on the repository, and there are no safety results or data sources.\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### LFM3-Omni-2B\n\n1. Start it with `llama-server -hf LiquidAI/LFM3-Omni-2B-GGUF:Q4_K_M --jinja` or `ollama run lfm3-omni`\n2. Greedy decoding for text. For speech use audio_temperature 0.4 and audio_repetition_penalty 1.2, per the card\n3. The context is 32K, and llama.cpp samples video at 2 frames a second up to 384 frames\n4. Parse tool calls yourself from the XML it returns\n5. It doesn't reason, so don't pass enable_thinking\n6. Validate JSON output yourself\n\n## Questions\n\n### Which is better for AI agents, Darwin-36B-Opus or LFM3-Omni-2B?\n\nDarwin-36B-Opus and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-omni-2b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"darwin-36b-opus\", \"b\": \"lfm3-omni-2b\"}`. From a terminal: `anchor compare darwin-36b-opus lfm3-omni-2b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/lfm3-omni-2b.json\n\n## Other comparisons with Darwin-36B-Opus or LFM3-Omni-2B\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 LFM3-Omni-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-omni-2b.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 LFM3-Omni-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-omni-2b.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 LFM3-Omni-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-omni-2b.md)\n- [Arete-27B vs 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