{
  "data": {
    "a": {
      "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",
      "dns": "inkling.grade.anchorterminal.com",
      "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": "2026-11-02"
      },
      "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": 64.7,
        "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": 1518,
        "categoryRank": 14,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "capability": 60,
          "interface": 85,
          "reach": 50,
          "risk": 70,
          "upkeep": 87
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-02"
        },
        "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 12 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": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 64.7
          }
        ],
        "editorialScores": {
          "capability": 60,
          "interface": 85,
          "reach": 50,
          "risk": 70,
          "upkeep": 87
        },
        "provenanceScore": 71,
        "checked": {
          "categories": {
            "capability": "2026-11-02",
            "interface": "2026-11-02",
            "reach": "2026-11-02",
            "risk": "2026-11-02",
            "upkeep": "2026-11-02"
          },
          "last": "2026-11-02",
          "lastMoved": "2026-11-02",
          "oldest": "2026-11-02",
          "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-2-small",
        "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": 71
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling.json",
      "live": {
        "slug": "inkling",
        "securityTxt": {
          "url": "https://thinkingmachines.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2029-07-13T07:00:00.000Z",
          "checkedAt": "2026-11-10T16:08:06.712462129Z"
        },
        "domain": {
          "domain": "thinkingmachines.ai",
          "registered": "2024-07-09",
          "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai",
          "checkedAt": "2026-11-08T15:05:10.558189316Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/thinkingmachines/Inkling/commits/main",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-10T16:23:50.70345348Z",
            "changedAt": "2026-11-10T16:23:50.70345348Z",
            "fingerprint": "60baeb3c18bc"
          }
        ],
        "updatedAt": "2026-11-10T16:23:50.70345348Z"
      }
    },
    "answer": "Inkling scores 64.7 (B) on agent readiness against North Mini Code 1.0's 61 (C), and leads in 2 of 4 scored categories. North Mini Code 1.0 leads on reach.",
    "b": {
      "slug": "north-mini-code-1-0",
      "name": "North Mini Code 1.0",
      "vendor": "Cohere",
      "vendorUrl": "https://cohere.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "North Mini Code 1.0 is Cohere's open-weight coding agent model, a mixture of experts of 30B parameters with 3B active, trained for tool use, with interleaved thinking and a 256K context. Apache 2.0. Cohere's 4-bit build is 19 GB.",
      "url": "https://www.anchorterminal.com/tools/north-mini-code-1-0",
      "markdownUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.json",
      "dns": "north-mini-code-1-0.grade.anchorterminal.com",
      "repo": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0"
        },
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0-fp8"
        },
        {
          "registry": "huggingface",
          "name": "CohereLabs/North-Mini-Code-1.0-w4a16"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the repositories is gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under Apache 2.0. The card calls it a research release. Running it yourself takes 19.4 GB at 4 bits (w4a16), 32.1 GB in FP8 or 61.0 GB in BF16 (checked 2026-11-10).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "agentic",
        "reasoning",
        "tool-calling",
        "long-context",
        "apache-2.0",
        "safetensors",
        "fp8",
        "4-bit",
        "self-hosted"
      ],
      "lastRelease": "2026-07-29",
      "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": 63,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 85,
          "risk": 60,
          "upkeep": 36
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.",
        "bestFor": "Developers who want a coding agent on their own GPU with a permissive licence",
        "strengths": [
          "Trained for tool use in coding agents, with parsers in released vLLM",
          "19 GB at 4 bits from Cohere, and a 256K context",
          "Apache 2.0, ungated",
          "Four released runtimes carry the architecture",
          "Tool use documented with a worked example"
        ],
        "weaknesses": [
          "No limitations, safety results, languages or data description on the card",
          "No reply from Cohere on the repository's discussions",
          "The card's instructions still point at unreleased vLLM and Transformers",
          "No GGUF from Cohere",
          "Text only",
          "No hosted API named"
        ],
        "agentNotes": [
          "Serve it with vLLM 0.33.0 or later and `--tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice`, with `cohere_melody` installed",
          "Pass the model's thinking back with its tool calls on every turn. The card says results drop without it",
          "Describe tools in JSON schema and append tool results as a dictionary with the tool role",
          "Use temperature 1.0 and top_p 0.95",
          "For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's",
          "It's text only. Don't send images"
        ],
        "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": 85,
          "reach": 85,
          "risk": 60,
          "upkeep": 36
        },
        "provenanceScore": 75,
        "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": "pip install \"vllm\u003e=0.33.0\" \"cohere_melody\u003e=0.9.0\"\nvllm serve CohereLabs/North-Mini-Code-1.0 -tp 2 --max-model-len 320000 --tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice",
        "http": "# vLLM serves an OpenAI-compatible API at http://localhost:8000/v1. Use temperature 1.0 and top_p 0.95,\n# and send the model's earlier thinking back with each turn"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/north-mini-code-1-0"
      },
      "sameCompany": [
        "cohere-chat",
        "cohere-embed",
        "cohere-transcribe-03-2026",
        "cohere-north"
      ],
      "weights": {
        "trainedBy": "Cohere and Cohere Labs",
        "params": "30B",
        "active": "3B",
        "context": 256000,
        "goodFor": "A local coding agent: repository work, terminal tasks and long tool-calling sessions, on one 24 GB GPU at 4 bits.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "North-Mini-Code-1.0-w4a16",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0-w4a16",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 19.38,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "Cohere's 4-bit weight build"
          },
          {
            "name": "unsloth North-Mini-Code-1.0-GGUF (UD-Q4_K_M)",
            "url": "https://huggingface.co/unsloth/North-Mini-Code-1.0-GGUF",
            "who": "unsloth",
            "precision": "q4_k_m",
            "sizeGB": 19.2,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Cohere's. 19.20 GB of UD-Q4_K_M weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "North-Mini-Code-1.0-fp8",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0-fp8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 32.06,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ],
            "note": "Cohere's FP8 build"
          },
          {
            "name": "unsloth North-Mini-Code-1.0-GGUF (Q8_0)",
            "url": "https://huggingface.co/unsloth/North-Mini-Code-1.0-GGUF",
            "who": "unsloth",
            "precision": "q8_0",
            "sizeGB": 32.44,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Cohere's. 32.44 GB of Q8_0 weights, from the Hub's model information on 10 November 2026. Reach doesn't count it"
          },
          {
            "name": "North-Mini-Code-1.0 (BF16 safetensors)",
            "url": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 60.97,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ],
            "note": "49 files"
          }
        ],
        "run": "vllm serve CohereLabs/North-Mini-Code-1.0-w4a16 --tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice",
        "runBuild": "North-Mini-Code-1.0-w4a16",
        "checked": "2026-11-10",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "Cohere (Cohere Labs)",
        "family": "North Mini Code",
        "url": "https://www.anchorterminal.com/open-weights/#cohere",
        "olderCount": 29
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Cohere Inc.",
        "domain": "cohere.com",
        "domainRegistered": "2000-03-07",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/CohereLabs/North-Mini-Code-1.0/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "The card says Developed by Cohere and Cohere Labs. Legal entity, domain and security facts are carried from our other Cohere listings.",
          "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored.",
          "The changelog is the commit history, 8 commits from 5 to 15 June 2026."
        ],
        "score": 75
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/north-mini-code-1-0.json"
    },
    "edges": [
      {
        "by": 51,
        "category": "upkeep",
        "leads": "inkling",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page. Training data 15, an EU training-content summary with sources, mix, a July 2026 collection cut-off and filtering. Last change 20, the weights files last changed on 23 July 2026, and Thinking Machines' Inkling renderer in tinker-cookbook changed on 30 October 2026, 3 days ago. Responsiveness 20, Thinking Machines answered 8 of the 12 questions and reports in its discussions. Version policy 5, a first release. File health 10, the files agree and the reports were answered.",
          "b": "Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, the card gives the training method and nothing about the data. Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (7 June to 6 November 2026) has a reply from a CohereLabs member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, with each build in its own repository. File health 10, Config, template and card agree on the architecture, and the June commit that removed broken templates says so. 11 + 0 + 10 + 0 + 5 + 10 = 36."
        },
        "scores": {
          "a": 87,
          "b": 36
        }
      },
      {
        "by": 35,
        "category": "reach",
        "leads": "north-mini-code-1-0",
        "name": "Reach",
        "reasons": {
          "a": "Memory 0 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 592.0 GB, about 710 GB with a fifth added, far above 256 GB. Runtimes 15, released Transformers, vLLM and SGLang run it, llama.cpp, Ollama and LM Studio don't. Builds 10, one quantised build (NVFP4). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Together AI, Fireworks and DeepInfra are live on Hugging Face, and Thinking Machines' Tinker serves it too.",
          "b": "Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB. Unsloth's GGUF isn't read for this line. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the cohere2_moe model, and llama.cpp b12242 has the cohere2moe architecture. Builds 15, Quantised builds from Cohere at two precisions, FP8 and 4-bit weights (w4a16), each in its own repository. Terms 15, Apache 2.0 in the metadata and on the card, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 25 + 20 + 15 + 15 + 10 + 0 = 85."
        },
        "scores": {
          "a": 50,
          "b": 85
        }
      },
      {
        "by": 10,
        "category": "risk",
        "leads": "inkling",
        "name": "Risk",
        "reasons": {
          "a": "File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT and FORTRESS results and commissioned external testers who published nothing. Agent guidance 10, the card says what its refusals miss and which safeguards to add, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent.",
          "b": "File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Cohere's verified CohereLabs organisation, which cohere.com links to per our other Cohere listings (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, Cohere's trust centre holds a responsible disclosure policy with a bug bounty, as recorded on our Cohere listings (5). 25 + 15 + 0 + 0 + 15 + 5 = 60."
        },
        "scores": {
          "a": 70,
          "b": 60
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "Cohere",
        "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": "2026-07-23",
        "b": "2026-07-29",
        "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": "3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling scores 64.7 (B) on agent readiness against North Mini Code 1.0's 61 (C), and leads in 2 of 4 scored categories. North Mini Code 1.0 leads on reach.",
        "question": "Which is better for AI agents, Inkling or North Mini Code 1.0?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 70 against 60",
          "Documentation and upkeep, 87 against 36"
        ],
        "also": null,
        "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"
      },
      {
        "aheadOn": [
          "Reach, 85 against 50"
        ],
        "also": null,
        "goodFor": "Developers who want a coding agent on their own GPU with a permissive licence",
        "slug": "north-mini-code-1-0",
        "watchFor": "No limitations, safety results, languages or data description on the card"
      }
    ],
    "history": {
      "inkling": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-02",
          "delta": 0.5,
          "from": 64.2,
          "fromGrade": "B",
          "to": 64.7,
          "toGrade": "B"
        }
      ],
      "north-mini-code-1-0": null
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
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      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-north-mini-code-1-0.json",
        "title": "Agents-A1-4B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-north-mini-code-1-0"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-north-mini-code-1-0"
      },
      {
        "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/apodex-1-1-mini-vs-north-mini-code-1-0.json",
        "title": "Apodex-1.1-mini vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling.json",
        "title": "Arete-27B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0.json",
        "title": "Arete-27B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.json",
        "title": "BigBang-v1 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0.json",
        "title": "BigBang-v1 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-north-mini-code-1-0.json",
        "title": "Carbon-X vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0"
      },
      {
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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/cosmos-reason2-2b-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-north-mini-code-1-0"
      },
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-north-mini-code-1-0"
      },
      {
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        "title": "DeepSeek V4.1 Flash vs Inkling",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling"
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      },
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-north-mini-code-1-0.json",
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      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0"
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      {
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-north-mini-code-1-0"
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-north-mini-code-1-0"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling"
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      {
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      },
      {
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      },
      {
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling"
      },
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0.json",
        "title": "Granite 4.2 8B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling.json",
        "title": "Hy-Memory-30B-A3B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-north-mini-code-1-0.json",
        "title": "Hy-Memory-30B-A3B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-inkling.json",
        "title": "Hy3 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-north-mini-code-1-0.json",
        "title": "Hy3 vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0.json",
        "title": "Inkling-Small vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small.json",
        "title": "Inkling vs Inkling-Small",
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Inkling vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3.json",
        "title": "Inkling vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3-1-pro.json",
        "title": "Inkling vs Kimi K3.1 Pro",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3-1-pro"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-kolibri-1.json",
        "title": "Inkling vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-kolibri-1"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-kronos.json",
        "title": "Inkling vs Kronos",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-kronos"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1.json",
        "title": "Inkling vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.json",
        "title": "Inkling vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1.json",
        "title": "Inkling vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lbs-27b.json",
        "title": "Inkling vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lbs-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.json",
        "title": "Inkling vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b.json",
        "title": "Inkling vs LFM3-1.7B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-audio-2b.json",
        "title": "Inkling vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-audio-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-omni-2b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-omni-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-vl-2b.json",
        "title": "Inkling vs LFM3-VL-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-vl-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-0-tiny.json",
        "title": "Inkling vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-0-tiny"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-1-flash-1019.json",
        "title": "Inkling vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-1-flash-1019"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-longcat-2-5.json",
        "title": "Inkling vs LongCat-2.5",
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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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-flash-rl.json",
        "title": "Inkling vs MiMo-V2.6-Flash-RL",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-flash-rl"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-1b.json",
        "title": "Inkling vs MiniCPM-V 4.7 1B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-1b"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Inkling vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json",
        "title": "Inkling vs MiniCPM5-2B",
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m3-1-flash.json",
        "title": "Inkling vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m3-1-flash"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4.json",
        "title": "Inkling vs Mistral Large 4",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-2-3b.json",
        "title": "Inkling vs Nanbeige4.2-3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-2-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-3-33b.json",
        "title": "Inkling vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-3-33b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-5-bolt-e4b-4gb.json",
        "title": "Inkling vs NVIDIA Nemotron 3.5 Bolt E4B 4GB",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-5-bolt-e4b-4gb"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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        "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"
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        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.json",
        "title": "Inkling vs occamy-1.0",
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.json",
        "title": "Inkling vs Olmo 3 7B Think",
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b.json",
        "title": "Inkling vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-otel-2-0-llm-31b-it.json",
        "title": "Inkling vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-otel-2-0-llm-31b-it"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen-agentworld-35b-a3b.json",
        "title": "Inkling vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen-agentworld-35b-a3b"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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        "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"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint.json",
        "title": "Inkling vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-recursive-flint"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ripple-65b-preview.json",
        "title": "Inkling vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-ripple-65b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.json",
        "title": "Inkling vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview"
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      {
        "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"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-step-3-7-flash.json",
        "title": "Inkling vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-step-3-7-flash"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-unlimited-ocr-2.json",
        "title": "Inkling vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-unlimited-ocr-2"
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      {
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      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ripple-65b-preview.json",
        "title": "North Mini Code 1.0 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-sensenova-loop-9b-preview.json",
        "title": "North Mini Code 1.0 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-smollm3-3b.json",
        "title": "North Mini Code 1.0 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-spark-x2-6-4b.json",
        "title": "North Mini Code 1.0 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-step-3-7-flash.json",
        "title": "North Mini Code 1.0 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-swift-1-5-qwen3-8-27b.json",
        "title": "North Mini Code 1.0 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "North Mini Code 1.0 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-thinkingcap-qwen3-8-27b.json",
        "title": "North Mini Code 1.0 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-unlimited-ocr-2.json",
        "title": "North Mini Code 1.0 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-wevisone-vl-2b.json",
        "title": "North Mini Code 1.0 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-wevisone-vl-4b.json",
        "title": "North Mini Code 1.0 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-zaya1-8b.json",
        "title": "North Mini Code 1.0 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 35,
        "edge": "north-mini-code-1-0",
        "inkling": 50,
        "key": "reach",
        "name": "Reach",
        "north-mini-code-1-0": 85,
        "weight": 25
      },
      {
        "by": 10,
        "edge": "inkling",
        "inkling": 70,
        "key": "risk",
        "name": "Risk",
        "north-mini-code-1-0": 60,
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "inkling": 85,
        "key": "interface",
        "name": "Agent interface",
        "north-mini-code-1-0": 85,
        "weight": 10
      },
      {
        "by": 51,
        "edge": "inkling",
        "inkling": 87,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "north-mini-code-1-0": 36,
        "weight": 10
      }
    ],
    "summary": "Inkling scores 64.7 (B) on agent readiness against North Mini Code 1.0's 61 (C), and leads in 2 of 4 scored categories. North Mini Code 1.0 leads on reach. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "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.",
      "north-mini-code-1-0": "A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0",
    "json": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.min.md"
  },
  "markdown": "Inkling scores 64.7 (B) on agent readiness against North Mini Code 1.0's 61 (C), and leads in 2 of 4 scored categories. North Mini Code 1.0 leads on reach. Both do open-weight models you run yourself.\n\n- Inkling: grade B, 64.7/100, rank #19 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling.json\n- North Mini Code 1.0: grade C, 61/100, rank #80 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/north-mini-code-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.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### 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 60\n- Documentation and upkeep, 87 against 36\n\nWatch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation\n\n### North Mini Code 1.0 (C)\n\nGood for: Developers who want a coding agent on their own GPU with a permissive licence\n\nAhead on:\n- Reach, 85 against 50\n\nWatch for: No limitations, safety results, languages or data description on the card\n\n\n## Why the edge\n\n### Documentation and upkeep: Inkling +51\n\n- Inkling (87): Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page. Training data 15, an EU training-content summary with sources, mix, a July 2026 collection cut-off and filtering. Last change 20, the weights files last changed on 23 July 2026, and Thinking Machines' Inkling renderer in tinker-cookbook changed on 30 October 2026, 3 days ago. Responsiveness 20, Thinking Machines answered 8 of the 12 questions and reports in its discussions. Version policy 5, a first release. File health 10, the files agree and the reports were answered.\n- North Mini Code 1.0 (36): Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, the card gives the training method and nothing about the data. Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (7 June to 6 November 2026) has a reply from a CohereLabs member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, with each build in its own repository. File health 10, Config, template and card agree on the architecture, and the June commit that removed broken templates says so. 11 + 0 + 10 + 0 + 5 + 10 = 36.\n\n### Reach: North Mini Code 1.0 +35\n\n- Inkling (50): Memory 0 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 592.0 GB, about 710 GB with a fifth added, far above 256 GB. Runtimes 15, released Transformers, vLLM and SGLang run it, llama.cpp, Ollama and LM Studio don't. Builds 10, one quantised build (NVFP4). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Together AI, Fireworks and DeepInfra are live on Hugging Face, and Thinking Machines' Tinker serves it too.\n- North Mini Code 1.0 (85): Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB. Unsloth's GGUF isn't read for this line. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the cohere2_moe model, and llama.cpp b12242 has the cohere2moe architecture. Builds 15, Quantised builds from Cohere at two precisions, FP8 and 4-bit weights (w4a16), each in its own repository. Terms 15, Apache 2.0 in the metadata and on the card, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 25 + 20 + 15 + 15 + 10 + 0 = 85.\n\n### Risk: Inkling +10\n\n- Inkling (70): File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT and FORTRESS results and commissioned external testers who published nothing. Agent guidance 10, the card says what its refusals miss and which safeguards to add, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent.\n- North Mini Code 1.0 (60): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Cohere's verified CohereLabs organisation, which cohere.com links to per our other Cohere listings (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, Cohere's trust centre holds a responsible disclosure policy with a bug bounty, as recorded on our Cohere listings (5). 25 + 15 + 0 + 0 + 15 + 5 = 60.\n\n## Score by category\n\n| Category | Weight | Inkling | North Mini Code 1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 50 | 85 | North Mini Code 1.0 +35 |\n| Risk | 20% (20 this run) | 70 | 60 | Inkling +10 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 87 | 36 | Inkling +51 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.7 · B** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling | North Mini Code 1.0 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | Cohere |\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 | 2026-07-23 | 2026-07-29 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Inkling\n\n- +0.5 on 2 November 2026: product\n\n### North Mini Code 1.0\n\nNo score change since it was listed.\n\n## Verdicts\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**North Mini Code 1.0.** A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.\n\n## Before you call either\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### North Mini Code 1.0\n\n1. Serve it with vLLM 0.33.0 or later and `--tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice`, with `cohere_melody` installed\n2. Pass the model's thinking back with its tool calls on every turn. The card says results drop without it\n3. Describe tools in JSON schema and append tool results as a dictionary with the tool role\n4. Use temperature 1.0 and top_p 0.95\n5. For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's\n6. It's text only. Don't send images\n\n## Questions\n\n### Which is better for AI agents, Inkling or North Mini Code 1.0?\n\nInkling scores 64.7 (B) on agent readiness against North Mini Code 1.0's 61 (C), and leads in 2 of 4 scored categories. North Mini Code 1.0 leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling\", \"b\": \"north-mini-code-1-0\"}`. From a terminal: `anchor compare inkling north-mini-code-1-0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling.json and https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.json\n\n## Other comparisons with Inkling or North Mini Code 1.0\n\n- [Agents-A1-4B vs Inkling](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.md)\n- [Agents-A1-4B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/agents-a1-4b-vs-north-mini-code-1-0.md)\n- [Apertus v1.5 8B vs Inkling](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling.md)\n- [Apertus v1.5 8B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-north-mini-code-1-0.md)\n- [Apodex-1.1-mini vs Inkling](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.md)\n- [Apodex-1.1-mini vs North Mini Code 1.0](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-north-mini-code-1-0.md)\n- [Arete-27B vs Inkling](https://www.anchorterminal.com/compare/arete-27b-vs-inkling.md)\n- [Arete-27B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0.md)\n- [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md)\n- [BigBang-v1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0.md)\n- [Carbon-X vs Inkling](https://www.anchorterminal.com/compare/carbon-x-vs-inkling.md)\n- [Carbon-X vs North Mini Code 1.0](https://www.anchorterminal.com/compare/carbon-x-vs-north-mini-code-1-0.md)\n- [Cola2 vs Inkling](https://www.anchorterminal.com/compare/cola2-vs-inkling.md)\n- [Cola2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0.md)\n- [Cosmos-Reason2-2B vs Inkling](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.md)\n- [Cosmos-Reason2-2B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-north-mini-code-1-0.md)\n- [Darwin-36B-Opus vs Inkling](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.md)\n- [Darwin-36B-Opus vs North Mini Code 1.0](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-north-mini-code-1-0.md)\n- [DeepSeek-V3.2 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.md)\n- [DeepSeek-V3.2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-north-mini-code-1-0.md)\n- [DeepSeek V4.1 Flash vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling.md)\n- [DeepSeek V4.1 Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-north-mini-code-1-0.md)\n- [DeepSeek-V4-Flash-0731 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.md)\n- [DeepSeek-V4-Flash-0731 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-north-mini-code-1-0.md)\n- [Devstral Small 2 vs Inkling](https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling.md)\n- [Devstral Small 2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/devstral-small-2-vs-north-mini-code-1-0.md)\n- [DiffusionGemma 26B A4B IT vs Inkling](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.md)\n- [DiffusionGemma 26B A4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-north-mini-code-1-0.md)\n- [EXAONE 4.5 33B vs Inkling](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.md)\n- [EXAONE 4.5 33B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0.md)\n- [Gemma 4 12B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling.md)\n- [Gemma 4 12B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-north-mini-code-1-0.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 26B A4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 31B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling.md)\n- [Gemma 4 31B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 E2B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling.md)\n- [Gemma 4 E2B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-north-mini-code-1-0.md)\n- [Gemma 4 E4B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling.md)\n- [Gemma 4 E4B IT vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-north-mini-code-1-0.md)\n- 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    "description": "Inkling scores 64.7 (B) to North Mini Code 1.0's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
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