{
  "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",
      "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 no LICENSE file. 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 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "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": 1197,
        "categoryRank": 30,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 80,
          "risk": 55,
          "upkeep": 51
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "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 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, base and evaluation method disagree with the files",
          "Tool calling and structured output aren't documented, and the card names no parser",
          "No LICENSE file, and 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": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 80,
          "risk": 55,
          "upkeep": 51
        },
        "provenanceScore": 40,
        "checked": {
          "categories": {
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "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": [
          {
            "name": "Darwin-35B-A3B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-35B-A3B-Opus",
            "params": "35B total, 3B active (MoE; 35,951,822,704 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-9B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-9B-Opus",
            "params": "9B (9,653,104,368 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-31B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-31B-Opus",
            "params": "31B (31,273,088,876 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-4B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-4B-Opus",
            "params": "4B (7,996,156,490 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-2B-webgpu",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-2B-webgpu",
            "params": "2B (Gemma 4 E2B)"
          },
          {
            "name": "Darwin-4B-David",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-4B-David",
            "params": "4B (7,996,156,490 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-4B-Genesis",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-4B-Genesis",
            "params": "4B (7,518,069,034 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-KR",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-KR",
            "params": "27B (27,781,427,952 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-Opus",
            "params": "27B (27,781,427,952 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-KR-V2",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-KR-V2",
            "params": "27B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-KR-V3",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-KR-V3",
            "params": "27B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-TTS-1.7B-Cross",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-TTS-1.7B-Cross",
            "params": "1.7B (2,099,234,881 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-2B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-2B-Opus",
            "params": "2B (1,881,825,088 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-28B-NEG",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-NEG",
            "params": "28B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-28B-Opus",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-Opus",
            "params": "28B (27B-class; 27,781,427,952 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-9B-NEG",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-9B-NEG",
            "params": "9B (9,653,104,368 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-28B-KR",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-KR",
            "params": "28B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "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)"
          },
          {
            "name": "Darwin-9B-NEG-x-Negentropy-V8",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-9B-NEG-x-Negentropy-V8",
            "params": "9B (8,953,803,264 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-Mistral-G1",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-Mistral-G1",
            "params": "123B-class (Ministral3ForCausalLM; 125,025,988,608 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-28B-REASON",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-REASON",
            "params": "28B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-28B-Coder",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-28B-Coder",
            "params": "28B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-218B-Delphi",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-218B-Delphi",
            "params": "218B (218,750,277,872 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-218B-Expert-Bio",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-218B-Expert-Bio",
            "params": "218B (218,750,277,872 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-218B-kr",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-218B-kr",
            "params": "218B (218,750,277,872 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-218B-Expert",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-218B-Expert",
            "params": "218B (218,750,277,872 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-60B-DUO",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-60B-DUO",
            "params": "60B (two ~30B models together)"
          },
          {
            "name": "Darwin-397B-JGOS",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-397B-JGOS",
            "params": "397B total, 17B active (MoE; 403,397,928,944 by the Hub's safetensors count)"
          },
          {
            "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)"
          },
          {
            "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)"
          },
          {
            "name": "Darwin-V9-Chimera-4B",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-V9-Chimera-4B",
            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-V9-Chimera-4B-SFT",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-V9-Chimera-4B-SFT",
            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-36B-KR",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-36B-KR",
            "params": "36B (35B total, 3B active, MoE; 35,951,822,704 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-397B-ZTC",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-397B-ZTC",
            "params": "397B (MoE, FP8; 403,586,672,624 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-4B-Chimera",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-4B-Chimera",
            "params": "4B (4,022,468,096 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-Chimera-4B-MoE-2E-PoC",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-Chimera-4B-MoE-2E-PoC",
            "params": "4B (8,735,845,376 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-V9-Chimera-4B-MoE3",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-V9-Chimera-4B-MoE3",
            "params": "4B (9,403,579,137 by the Hub's safetensors count)"
          },
          {
            "name": "Darwin-27B-RSI",
            "url": "https://huggingface.co/FINAL-Bench/Darwin-27B-RSI",
            "params": "27B (26,895,998,464 by the Hub's safetensors count)"
          },
          {
            "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": "2026-10-21",
        "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 only, with no licence 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": 40
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/darwin-36b-opus.json"
    },
    "answer": "Inkling scores 64.2 (B) on agent readiness against Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach.",
    "b": {
      "slug": "inkling",
      "name": "Inkling",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling is Thinking Machines Lab's large open-weight mixture-of-experts model, 975B total and 41B active parameters, taking text, images and audio and returning text, with adjustable thinking effort, published in BF16 and NVFP4 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling.json",
      "repo": "https://huggingface.co/thinkingmachines/Inkling",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-NVFP4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 1,904.8 GB for the BF16 files and 592.0 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $1.00 per million input tokens and $4.05 per million output tokens (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "audio",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-23",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.2,
        "grade": "B",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 16,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 60,
          "interface": 85,
          "reach": 50,
          "risk": 70,
          "upkeep": 82
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results.",
        "bestFor": "Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.",
        "strengths": [
          "Three inference providers and Thinking Machines' own Tinker host it today",
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request, several tool calls a turn and a 1M-token context",
          "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers",
          "Thinking Machines answered 8 of the 13 questions and reports in its discussions",
          "A training-content summary with sources, mix and a July 2026 collection cut-off"
        ],
        "weaknesses": [
          "The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "No release of ggml-org's llama.cpp, Ollama or LM Studio runs it",
          "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance",
          "Structured output isn't documented, and the card gives no dated knowledge cut-off"
        ],
        "agentNotes": [
          "Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it",
          "On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`",
          "Use the inkling tool parser, not Hermes, and the inkling reasoning parser",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs list xhigh",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card",
          "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.2
          }
        ],
        "editorialScores": {
          "capability": 60,
          "interface": 85,
          "reach": 50,
          "risk": 70,
          "upkeep": 82
        },
        "provenanceScore": 67,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, NVFP4 on 8 B200 GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 \\\n  --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-NVFP4\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling"
      },
      "sameCompany": [
        "inkling-small"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "975B",
        "active": "41B",
        "context": 1048576,
        "goodFor": "Large mixture-of-experts generalist for coding, agents, factual recall and audio, with images in and thinking effort set per request.",
        "runtimes": [
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Inkling-NVFP4",
            "url": "https://huggingface.co/thinkingmachines/Inkling-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 592,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "NVFP4 experts with FP8 and BF16 parts. Thinking Machines says W4A4 needs NVIDIA SM100 or newer, and W4A16 runs on H200"
          },
          {
            "name": "Inkling",
            "url": "https://huggingface.co/thinkingmachines/Inkling",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 1904.8,
            "memoryGB": 4096,
            "format": "safetensors",
            "note": "1,904.8 GB × 1.2 = 2,285.7 GB, so the 4,096 GB band. Thinking Machines states at least 2 TB of GPU memory"
          }
        ],
        "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling",
        "runBuild": "Inkling-NVFP4",
        "checked": "2026-10-21",
        "minMemoryGB": 1024
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines",
        "others": [
          {
            "name": "Inkling-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-Small",
            "params": "265.96B (Hub safetensors count; the name states none)",
            "listing": "https://www.anchorterminal.com/tools/inkling-small"
          }
        ],
        "unrestrictedCopies": 1
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "thinkingmachines.ai's registration date wasn't read on 21 October 2026.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "Thinking Machines' Inkling page links the thinkingmachines collection on Hugging Face, and its model card page links the repository. Hugging Face hasn't verified the organisation.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 13 commits from 15 to 23 July 2026, the upload, a Transformers processor and template change on 15 July, card updates and community evaluation results.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, and the site publishes a coordinated vulnerability disclosure policy that leaves model safety to a separate incident contact."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "FINAL-Bench (VIDRAFT)",
        "b": "Thinking Machines Lab",
        "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": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-04-23",
        "b": "2026-07-23",
        "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": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.5/5 (4)",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling scores 64.2 (B) on agent readiness against Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach.",
        "question": "Which is better for AI agents, Darwin-36B-Opus or Inkling?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 80 against 50"
        ],
        "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, 70 against 55",
          "Agent interface, 85 against 70",
          "Documentation and upkeep, 82 against 51"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.0 against 2.5 out of 5"
        ],
        "goodFor": "Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.",
        "slug": "inkling",
        "watchFor": "The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation"
      }
    ],
    "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-inkling.json",
        "title": "Agents-A1-4B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling"
      },
      {
        "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-inkling.json",
        "title": "Apertus v1.5 8B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.json",
        "title": "Apodex-1.1-mini vs Inkling",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus"
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      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v3-2.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v4-1-flash"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Inkling vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5.json",
        "title": "Inkling vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json",
        "title": "Inkling vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5.json",
        "title": "Inkling vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.json",
        "title": "Inkling vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b.json",
        "title": "Inkling vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Inkling vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Inkling vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-4b.json",
        "title": "Inkling vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Inkling vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-super-120b-a12b.json",
        "title": "Inkling vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Inkling vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.json",
        "title": "Inkling vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.json",
        "title": "Inkling vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-35b-a3b.json",
        "title": "Inkling vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-397b.json",
        "title": "Inkling vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-9b.json",
        "title": "Inkling vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Inkling vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507.json",
        "title": "Inkling vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-0-8b.json",
        "title": "Inkling vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b.json",
        "title": "Inkling vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-2b.json",
        "title": "Inkling vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-397b-a17b.json",
        "title": "Inkling vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b.json",
        "title": "Inkling vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-9b.json",
        "title": "Inkling vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-27b.json",
        "title": "Inkling vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-35b-a3b.json",
        "title": "Inkling vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-27b.json",
        "title": "Inkling vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-flash-next.json",
        "title": "Inkling vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Inkling vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-next.json",
        "title": "Inkling vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Inkling vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-2b-instruct.json",
        "title": "Inkling vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Inkling vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct.json",
        "title": "Inkling vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct.json",
        "title": "Inkling vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct.json",
        "title": "Inkling vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Inkling vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-smollm3-3b.json",
        "title": "Inkling vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-spark-x2-6-4b.json",
        "title": "Inkling vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Inkling vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Inkling vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Inkling vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 30,
        "darwin-36b-opus": 80,
        "edge": "darwin-36b-opus",
        "inkling": 50,
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 15,
        "darwin-36b-opus": 55,
        "edge": "inkling",
        "inkling": 70,
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 15,
        "darwin-36b-opus": 70,
        "edge": "inkling",
        "inkling": 85,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 31,
        "darwin-36b-opus": 51,
        "edge": "inkling",
        "inkling": 82,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Inkling scores 64.2 (B) on agent readiness against Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach. Both do open-weight models you run yourself.",
    "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.",
      "inkling": "Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling",
    "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.min.md"
  },
  "markdown": "Inkling scores 64.2 (B) on agent readiness against Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach. Both do open-weight models you run yourself.\n\n- Darwin-36B-Opus: grade C, 61/100, rank #37 of 100 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- Inkling: grade B, 64.2/100, rank #20 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling.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 2870 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 50\n\nWatch for: The merge method is proprietary and the current weights include an undescribed targeted refinement\n\n### Inkling (B)\n\nGood for: Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.\n\nAhead on:\n- Risk, 70 against 55\n- Agent interface, 85 against 70\n- Documentation and upkeep, 82 against 51\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 2.5 out of 5\n\nWatch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation\n\n\n## Score by category\n\n| Category | Weight | Darwin-36B-Opus | Inkling | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 80 | 50 | Darwin-36B-Opus +30 |\n| Risk | 20% (20 this run) | 55 | 70 | Inkling +15 |\n| Agent interface | 10% (10 this run) | 70 | 85 | Inkling +15 |\n| Documentation and upkeep | 10% (10 this run) | 51 | 82 | Inkling +31 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **64.2 · B** | |\n\n## Facts side by side\n\n| Fact | Darwin-36B-Opus | Inkling |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | FINAL-Bench (VIDRAFT) | Thinking Machines Lab |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-04-23 | 2026-07-23 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 2.5/5 (4) | 3/5 (4) |\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**Inkling.** Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n## Before you call either\n\n### Darwin-36B-Opus\n\n1. Quickest start is `llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja`, about 21 GB of files\n2. On the reference machine BF16 fits, `vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parsers for Qwen3.6's format\n3. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention\n4. The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces\n5. generation_config.json stops only on the end-of-text token, so add `\u003c|im_end|\u003e` as a stop token if a runtime keeps generating after the turn ends\n6. Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files\n7. Validate JSON output yourself, since structured output isn't documented\n\n### Inkling\n\n1. Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it\n2. On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`\n3. Use the inkling tool parser, not Hermes, and the inkling reasoning parser\n4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs list xhigh\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card\n7. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n## Questions\n\n### Which is better for AI agents, Darwin-36B-Opus or Inkling?\n\nInkling scores 64.2 (B) on agent readiness against Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"darwin-36b-opus\", \"b\": \"inkling\"}`. From a terminal: `anchor compare darwin-36b-opus inkling`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/inkling.json\n\n## Other comparisons with Darwin-36B-Opus or Inkling\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 Inkling](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.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 Inkling](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling.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 Inkling](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.md)\n- [BigBang-v1 vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus.md)\n- [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md)\n- [Cosmos-Reason2-2B vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus.md)\n- [Cosmos-Reason2-2B vs Inkling](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.md)\n- [Darwin-36B-Opus vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v3-2.md)\n- [Darwin-36B-Opus vs DeepSeek V4.1 Flash](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v4-1-flash.md)\n- [Darwin-36B-Opus vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v4-flash-0731.md)\n- [Darwin-36B-Opus vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-diffusiongemma-26b-a4b-it.md)\n- [Darwin-36B-Opus vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gemma-4-12b-it.md)\n- [Darwin-36B-Opus vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gemma-4-26b-a4b-it.md)\n- [Darwin-36B-Opus vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gemma-4-31b-it.md)\n- [Darwin-36B-Opus vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gemma-4-e2b-it.md)\n- [Darwin-36B-Opus vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gemma-4-e4b-it.md)\n- [Darwin-36B-Opus vs GLM-4.5-Air](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-4-5-air.md)\n- [Darwin-36B-Opus vs GLM-4.7-Flash](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-4-7-flash.md)\n- [Darwin-36B-Opus vs GLM-5.3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3.md)\n- [Darwin-36B-Opus vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3-flash.md)\n- [Darwin-36B-Opus vs gpt-oss-120b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-120b.md)\n- [Darwin-36B-Opus vs gpt-oss-20b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-20b.md)\n- [Darwin-36B-Opus vs Granite 4.2 3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-granite-4-2-3b.md)\n- [Darwin-36B-Opus vs Hy3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-hy3.md)\n- [Darwin-36B-Opus vs Inkling-Small](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small.md)\n- [Darwin-36B-Opus vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Darwin-36B-Opus vs Kimi K3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kimi-k3.md)\n- [Darwin-36B-Opus vs Kolibri-1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kolibri-1.md)\n- [Darwin-36B-Opus vs Laguna M.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.md)\n- [Darwin-36B-Opus vs Laguna S 2.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1.md)\n- [Darwin-36B-Opus vs Laguna XS 2.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1.md)\n- [Darwin-36B-Opus vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm2-5-2-6b.md)\n- [Darwin-36B-Opus vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-0-tiny.md)\n- [Darwin-36B-Opus vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Darwin-36B-Opus vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-o-4-5.md)\n- [Darwin-36B-Opus vs MiniCPM5-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm5-2b.md)\n- [Darwin-36B-Opus vs MiniMax-M2.5](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-5.md)\n- [Darwin-36B-Opus vs MiniMax-M2.7](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-7.md)\n- [Darwin-36B-Opus vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-muse-glimmer-30b.md)\n- [Darwin-36B-Opus vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-nano-30b-a3b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-nano-4b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Darwin-36B-Opus vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-super-120b-a12b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-ultra-550b-a55b.md)\n- [Darwin-36B-Opus vs occamy-1.0](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0.md)\n- [Darwin-36B-Opus vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-olmo-3-7b-think.md)\n- [Darwin-36B-Opus vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-35b-a3b.md)\n- [Darwin-36B-Opus vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-397b.md)\n- [Darwin-36B-Opus vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-9b.md)\n- [Darwin-36B-Opus vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Darwin-36B-Opus vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-4b-instruct-2507.md)\n- [Darwin-36B-Opus vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-0-8b.md)\n- [Darwin-36B-Opus vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-122b-a10b.md)\n- [Darwin-36B-Opus vs Qwen3.5-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-2b.md)\n- [Darwin-36B-Opus vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-397b-a17b.md)\n- [Darwin-36B-Opus vs Qwen3.5-4B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-4b.md)\n- [Darwin-36B-Opus vs Qwen3.5-9B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-5-9b.md)\n- [Darwin-36B-Opus vs Qwen3.6-27B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-6-27b.md)\n- [Darwin-36B-Opus vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-6-35b-a3b.md)\n- [Darwin-36B-Opus vs Qwen3.8-27B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-8-27b.md)\n- [Darwin-36B-Opus vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-8-flash-next.md)\n- [Darwin-36B-Opus vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-coder-next.md)\n- [Darwin-36B-Opus vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-2b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-32b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-4b-instruct.md)\n- [Darwin-36B-Opus vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwen3-vl-8b-instruct.md)\n- [Darwin-36B-Opus vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-qwopus3-8-27b-flash-v2.md)\n- [Darwin-36B-Opus vs SmolLM3-3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-smollm3-3b.md)\n- [Darwin-36B-Opus vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-spark-x2-6-4b.md)\n- [Darwin-36B-Opus vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-27b.md)\n- [Darwin-36B-Opus vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Darwin-36B-Opus vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-thinkingcap-qwen3-8-27b.md)\n- [DeepSeek-V3.2 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.md)\n- [DeepSeek V4.1 Flash vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling.md)\n- [DeepSeek-V4-Flash-0731 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.md)\n- [DiffusionGemma 26B A4B IT vs Inkling](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.md)\n- [Gemma 4 12B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling.md)\n- [Gemma 4 26B A4B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling.md)\n- [Gemma 4 31B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling.md)\n- [Gemma 4 E2B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling.md)\n- [Gemma 4 E4B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling.md)\n- [GLM-4.5-Air vs Inkling](https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling.md)\n- [GLM-4.7-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling.md)\n- [GLM-5.3-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.md)\n- [GLM-5.3 vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.md)\n- [gpt-oss-120b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling.md)\n- [gpt-oss-20b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling.md)\n- [Granite 4.2 3B vs Inkling](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling.md)\n- [Hy3 vs Inkling](https://www.anchorterminal.com/compare/hy3-vs-inkling.md)\n- [Inkling vs Inkling-Small](https://www.anchorterminal.com/compare/inkling-vs-inkling-small.md)\n- [Inkling vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Inkling vs Kimi K3](https://www.anchorterminal.com/compare/inkling-vs-kimi-k3.md)\n- [Inkling vs Kolibri-1](https://www.anchorterminal.com/compare/inkling-vs-kolibri-1.md)\n- [Inkling vs Laguna M.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1.md)\n- [Inkling vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.md)\n- [Inkling vs Laguna XS 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1.md)\n- [Inkling vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.md)\n- [Inkling vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/inkling-vs-ling-3-0-tiny.md)\n- [Inkling vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Inkling vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5.md)\n- [Inkling vs MiniCPM5-2B](https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.md)\n- [Inkling vs MiniMax-M2.5](https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5.md)\n- [Inkling vs MiniMax-M2.7](https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.md)\n- [Inkling vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b.md)\n- [Inkling vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Inkling vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-30b-a3b.md)\n- [Inkling vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-4b.md)\n- [Inkling vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Inkling vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-super-120b-a12b.md)\n- [Inkling vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-ultra-550b-a55b.md)\n- [Inkling vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.md)\n- [Inkling vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.md)\n- [Inkling vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-35b-a3b.md)\n- [Inkling vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-397b.md)\n- [Inkling vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-9b.md)\n- [Inkling vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Inkling vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507.md)\n- [Inkling vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-0-8b.md)\n- [Inkling vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-122b-a10b.md)\n- [Inkling vs Qwen3.5-2B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-2b.md)\n- [Inkling vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-397b-a17b.md)\n- [Inkling vs Qwen3.5-4B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b.md)\n- [Inkling vs Qwen3.5-9B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-9b.md)\n- [Inkling vs Qwen3.6-27B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-27b.md)\n- [Inkling vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-35b-a3b.md)\n- [Inkling vs Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-27b.md)\n- [Inkling vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-flash-next.md)\n- [Inkling vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Inkling vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/inkling-vs-qwen3-coder-next.md)\n- [Inkling vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Inkling vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-2b-instruct.md)\n- [Inkling vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Inkling vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct.md)\n- [Inkling vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct.md)\n- [Inkling vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct.md)\n- [Inkling vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/inkling-vs-qwopus3-8-27b-flash-v2.md)\n- [Inkling vs SmolLM3-3B](https://www.anchorterminal.com/compare/inkling-vs-smollm3-3b.md)\n- [Inkling vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/inkling-vs-spark-x2-6-4b.md)\n- [Inkling vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b.md)\n- [Inkling vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Inkling vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b.md)\n",
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      {
        "name": "Darwin-36B-Opus vs Inkling",
        "url": ""
      }
    ],
    "description": "Inkling scores 64.2 (B) to Darwin-36B-Opus's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
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    "h1": "Darwin-36B-Opus vs Inkling",
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