{
  "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 ZAYA1-8B's 61 (C), and leads in 3 of 4 scored categories. ZAYA1-8B leads on reach.",
    "b": {
      "slug": "zaya1-8b",
      "name": "ZAYA1-8B",
      "vendor": "Zyphra",
      "vendorUrl": "https://www.zyphra.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "ZAYA1-8B is Zyphra's open-weight reasoning model, a mixture of experts of 8.4B parameters with 760M active, trained from scratch for maths and coding. Apache 2.0. Zyphra's 4-bit build is 5.9 GB. Released SGLang and Transformers run it.",
      "url": "https://www.anchorterminal.com/tools/zaya1-8b",
      "markdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json",
      "dns": "zaya1-8b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/Zyphra/ZAYA1-8B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B"
        },
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B-FP8-Experts"
        },
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B-MXFP4-Experts"
        }
      ],
      "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, per the main repository's metadata. Running it yourself costs little: 5.9 GB with the experts at 4 bits (MXFP4), 9.6 GB in FP8 or 17.7 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/Zyphra/ZAYA1-8B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "small",
        "reasoning",
        "maths",
        "coding",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-02",
      "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": 67,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 60,
          "reach": 80,
          "risk": 55,
          "upkeep": 50
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.",
        "bestFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling",
        "strengths": [
          "Apache 2.0, ungated",
          "5.9 GB at 4 bits, 760M parameters active",
          "Released Transformers and SGLang carry the architecture",
          "Zyphra replied in most of the recent discussions",
          "The original checkpoint is kept beside the reshaped one"
        ],
        "weaknesses": [
          "Tool calling needs a parser that only Zyphra's vLLM fork has",
          "Released vLLM and llama.cpp don't run it, and there's no GGUF",
          "The card's install steps use forks",
          "No limitations, context length, languages, data or safety results on the card",
          "Benchmarks on the card are all from Zyphra's own harness"
        ],
        "agentNotes": [
          "Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork",
          "Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in",
          "Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work",
          "Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes",
          "The quantised repositories have no licence tag. The main one is Apache 2.0"
        ],
        "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": 60,
          "reach": 80,
          "risk": 55,
          "upkeep": 50
        },
        "provenanceScore": 56,
        "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 \"sglang\u003e=0.5.23\"\npython -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3\n# the card's own route is vLLM from Zyphra's fork, with --tool-call-parser zaya_xml",
        "http": "# SGLang serves an OpenAI-compatible API at http://localhost:30000/v1. The card recommends temperature 1.0\n# and top_p 0.95 in general, and temperature 0.6 for agent and code work"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/zaya1-8b"
      },
      "weights": {
        "trainedBy": "Zyphra",
        "builtOn": "ZAYA1-reasoning-base, Zyphra's own pre-trained model, per the card",
        "params": "8.4B",
        "active": "760M",
        "context": 131072,
        "goodFor": "Long step-by-step reasoning in maths and code on a small machine, and as the model inside a test-time compute harness.",
        "runtimes": [
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "ZAYA1-8B-MXFP4-Experts",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B-MXFP4-Experts",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 5.85,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "Zyphra's build with the experts at 4 bits. Which released runtime loads it wasn't established"
          },
          {
            "name": "ZAYA1-8B-FP8-Experts",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B-FP8-Experts",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 9.64,
            "memoryGB": 12,
            "format": "safetensors",
            "note": "Zyphra's build with the experts in FP8"
          },
          {
            "name": "ZAYA1-8B (BF16 safetensors)",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 17.68,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "SGLang",
              "Transformers"
            ],
            "note": "Four shards, reshaped for Transformers"
          }
        ],
        "run": "python -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3",
        "runBuild": "ZAYA1-8B (BF16 safetensors)",
        "checked": "2026-11-10",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Zyphra",
        "family": "ZAYA1",
        "url": "https://www.anchorterminal.com/open-weights/#zyphra",
        "others": [
          {
            "name": "ZAYA1-VL-8B",
            "url": "https://huggingface.co/Zyphra/ZAYA1-VL-8B"
          },
          {
            "name": "ZAYA1-74B-preview",
            "url": "https://huggingface.co/Zyphra/ZAYA1-74B-preview"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Zyphra, named on the card and its site. The legal entity wasn't looked up",
        "domain": "zyphra.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/Zyphra/ZAYA1-8B/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "www.zyphra.com's robots.txt allows reading outside /studio and /api. Its about page gives a San Francisco address and names no people in the text read.",
          "The domain's registration date wasn't looked up. www.zyphra.com has no security.txt (404 on 10 November 2026).",
          "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored. Zyphra's site lists a cloud product for its open models, which wasn't read.",
          "The changelog is the commit history, 41 commits from 4 May to 26 June 2026."
        ],
        "score": 56
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/zaya1-8b.json"
    },
    "edges": [
      {
        "by": 37,
        "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 5, Intended use and the parameter counts are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the main repository last changed on 26 June 2026 (the checkpoint reshaped for Transformers), 137 days before this check, and the quantised repositories on 2 July, 131 days. Responsiveness 20, Of the 16 most recent discussions that aren't pull requests (7 May to 14 August 2026), 10 have a reply from a Zyphra member, which is most. Version policy 5, the original checkpoint is kept as ZAYA1-8B-legacy and the card says so at the top, without a date. File health 10, Config, template and card agree on the architecture after the reshape. 5 + 0 + 10 + 20 + 5 + 10 = 50."
        },
        "scores": {
          "a": 87,
          "b": 50
        }
      },
      {
        "by": 30,
        "category": "reach",
        "leads": "zaya1-8b",
        "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 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, 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, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80."
        },
        "scores": {
          "a": 50,
          "b": 80
        }
      },
      {
        "by": 25,
        "category": "interface",
        "leads": "inkling",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.",
          "b": "Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60."
        },
        "scores": {
          "a": 85,
          "b": 60
        }
      },
      {
        "by": 15,
        "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 the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (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 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55."
        },
        "scores": {
          "a": 70,
          "b": 55
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "Zyphra",
        "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": "2026-07-02",
        "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 ZAYA1-8B's 61 (C), and leads in 3 of 4 scored categories. ZAYA1-8B leads on reach.",
        "question": "Which is better for AI agents, Inkling or ZAYA1-8B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 70 against 55",
          "Agent interface, 85 against 60",
          "Documentation and upkeep, 87 against 50"
        ],
        "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, 80 against 50"
        ],
        "also": null,
        "goodFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling",
        "slug": "zaya1-8b",
        "watchFor": "Tool calling needs a parser that only Zyphra's vLLM fork has"
      }
    ],
    "history": {
      "inkling": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-02",
          "delta": 0.5,
          "from": 64.2,
          "fromGrade": "B",
          "to": 64.7,
          "toGrade": "B"
        }
      ],
      "zaya1-8b": null
    },
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "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/agents-a1-4b-vs-zaya1-8b.json",
        "title": "Agents-A1-4B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-zaya1-8b"
      },
      {
        "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/apertus-v1-5-8b-vs-zaya1-8b.json",
        "title": "Apertus v1.5 8B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-zaya1-8b"
      },
      {
        "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-zaya1-8b.json",
        "title": "Apodex-1.1-mini vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-zaya1-8b"
      },
      {
        "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-zaya1-8b.json",
        "title": "Arete-27B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-zaya1-8b"
      },
      {
        "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-zaya1-8b.json",
        "title": "BigBang-v1 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling.json",
        "title": "Carbon-X vs Inkling",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-zaya1-8b.json",
        "title": "Carbon-X vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-inkling.json",
        "title": "Cola2 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b.json",
        "title": "Cola2 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json",
        "title": "Cosmos-Reason2-2B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-zaya1-8b.json",
        "title": "Cosmos-Reason2-2B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.json",
        "title": "Darwin-36B-Opus vs Inkling",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-zaya1-8b.json",
        "title": "Darwin-36B-Opus vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.json",
        "title": "DeepSeek-V3.2 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-zaya1-8b.json",
        "title": "DeepSeek-V3.2 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling.json",
        "title": "DeepSeek V4.1 Flash vs Inkling",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-zaya1-8b.json",
        "title": "DeepSeek V4.1 Flash vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.json",
        "title": "DeepSeek-V4-Flash-0731 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling"
      },
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-zaya1-8b.json",
        "title": "DeepSeek-V4-Flash-0731 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling.json",
        "title": "Devstral Small 2 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-zaya1-8b.json",
        "title": "Devstral Small 2 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.json",
        "title": "DiffusionGemma 26B A4B IT vs Inkling",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling"
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      {
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        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.json",
        "title": "EXAONE 4.5 33B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling"
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        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b"
      },
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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-4-12b-it-vs-zaya1-8b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-zaya1-8b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-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-zaya1-8b"
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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-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-zaya1-8b"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-zaya1-8b"
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      {
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-zaya1-8b"
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-zaya1-8b"
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      {
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-zaya1-8b"
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling"
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        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-zaya1-8b"
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling"
      },
      {
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        "title": "Granite 4.2 3B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-zaya1-8b"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-zaya1-8b.json",
        "title": "Hy-Memory-30B-A3B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-zaya1-8b"
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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-zaya1-8b.json",
        "title": "Hy3 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-zaya1-8b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-zaya1-8b.json",
        "title": "Inkling-Small vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-zaya1-8b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small.json",
        "title": "Inkling vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/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",
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        "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",
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        "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",
        "url": "https://www.anchorterminal.com/compare/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",
        "url": "https://www.anchorterminal.com/compare/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-north-mini-code-1-0.json",
        "title": "Inkling vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-north-mini-code-1-0"
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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",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b.json",
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        "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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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-wevisone-vl-2b.json",
        "title": "Inkling vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-wevisone-vl-2b"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-wevisone-vl-4b.json",
        "title": "Inkling vs WeVisOne-VL-4B",
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        "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b.json",
        "title": "Step 3.7 Flash vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-zaya1-8b.json",
        "title": "Swift 1.5 Qwen3.8-27B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-zaya1-8b.json",
        "title": "Swift 1.5 Qwen3.8-Flash-Next vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b.json",
        "title": "ThinkingCap (Qwen3.8 27B) vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b.json",
        "title": "Baidu Unlimited-OCR-2 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b.json",
        "title": "WeVisOne-VL-2B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.json",
        "title": "WeVisOne-VL-4B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 30,
        "edge": "zaya1-8b",
        "inkling": 50,
        "key": "reach",
        "name": "Reach",
        "weight": 25,
        "zaya1-8b": 80
      },
      {
        "by": 15,
        "edge": "inkling",
        "inkling": 70,
        "key": "risk",
        "name": "Risk",
        "weight": 20,
        "zaya1-8b": 55
      },
      {
        "by": 25,
        "edge": "inkling",
        "inkling": 85,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10,
        "zaya1-8b": 60
      },
      {
        "by": 37,
        "edge": "inkling",
        "inkling": 87,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10,
        "zaya1-8b": 50
      }
    ],
    "summary": "Inkling scores 64.7 (B) on agent readiness against ZAYA1-8B's 61 (C), and leads in 3 of 4 scored categories. ZAYA1-8B 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.",
      "zaya1-8b": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety."
    }
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  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b",
    "json": "https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.min.md"
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  "markdown": "Inkling scores 64.7 (B) on agent readiness against ZAYA1-8B's 61 (C), and leads in 3 of 4 scored categories. ZAYA1-8B 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- ZAYA1-8B: grade C, 61/100, rank #85 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/zaya1-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/zaya1-8b.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 55\n- Agent interface, 85 against 60\n- Documentation and upkeep, 87 against 50\n\nWatch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation\n\n### ZAYA1-8B (C)\n\nGood for: People who want a small, fast reasoning model for maths and code and can live without tool calling\n\nAhead on:\n- Reach, 80 against 50\n\nWatch for: Tool calling needs a parser that only Zyphra's vLLM fork has\n\n\n## Why the edge\n\n### Documentation and upkeep: Inkling +37\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- ZAYA1-8B (50): Model card 5, Intended use and the parameter counts are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the main repository last changed on 26 June 2026 (the checkpoint reshaped for Transformers), 137 days before this check, and the quantised repositories on 2 July, 131 days. Responsiveness 20, Of the 16 most recent discussions that aren't pull requests (7 May to 14 August 2026), 10 have a reply from a Zyphra member, which is most. Version policy 5, the original checkpoint is kept as ZAYA1-8B-legacy and the card says so at the top, without a date. File health 10, Config, template and card agree on the architecture after the reshape. 5 + 0 + 10 + 20 + 5 + 10 = 50.\n\n### Reach: ZAYA1-8B +30\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- ZAYA1-8B (80): Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, 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, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80.\n\n### Agent interface: Inkling +25\n\n- Inkling (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.\n- ZAYA1-8B (60): Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60.\n\n### Risk: Inkling +15\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- ZAYA1-8B (55): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (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 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.\n\n## Score by category\n\n| Category | Weight | Inkling | ZAYA1-8B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 50 | 80 | ZAYA1-8B +30 |\n| Risk | 20% (20 this run) | 70 | 55 | Inkling +15 |\n| Agent interface | 10% (10 this run) | 85 | 60 | Inkling +25 |\n| Documentation and upkeep | 10% (10 this run) | 87 | 50 | Inkling +37 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.7 · B** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling | ZAYA1-8B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | Zyphra |\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 | 2026-07-02 |\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### ZAYA1-8B\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**ZAYA1-8B.** A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.\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### ZAYA1-8B\n\n1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork\n2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in\n3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work\n4. Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes\n5. The quantised repositories have no licence tag. The main one is Apache 2.0\n\n## Questions\n\n### Which is better for AI agents, Inkling or ZAYA1-8B?\n\nInkling scores 64.7 (B) on agent readiness against ZAYA1-8B's 61 (C), and leads in 3 of 4 scored categories. ZAYA1-8B leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling\", \"b\": \"zaya1-8b\"}`. From a terminal: `anchor compare inkling zaya1-8b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling.json and https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json\n\n## Other comparisons with Inkling or ZAYA1-8B\n\n- [Agents-A1-4B vs Inkling](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.md)\n- [Agents-A1-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-zaya1-8b.md)\n- [Arete-27B vs Inkling](https://www.anchorterminal.com/compare/arete-27b-vs-inkling.md)\n- [Arete-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/arete-27b-vs-zaya1-8b.md)\n- [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md)\n- [BigBang-v1 vs ZAYA1-8B](https://www.anchorterminal.com/compare/bigbang-v1-vs-zaya1-8b.md)\n- [Carbon-X vs Inkling](https://www.anchorterminal.com/compare/carbon-x-vs-inkling.md)\n- [Carbon-X vs ZAYA1-8B](https://www.anchorterminal.com/compare/carbon-x-vs-zaya1-8b.md)\n- [Cola2 vs Inkling](https://www.anchorterminal.com/compare/cola2-vs-inkling.md)\n- [Cola2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b.md)\n- [Cosmos-Reason2-2B vs Inkling](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.md)\n- [Cosmos-Reason2-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-zaya1-8b.md)\n- [Darwin-36B-Opus vs Inkling](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.md)\n- [Darwin-36B-Opus vs 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Inkling](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.md)\n- [DiffusionGemma 26B A4B IT vs ZAYA1-8B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-zaya1-8b.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 ZAYA1-8B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-zaya1-8b.md)\n- [GLM-4.5-Air vs Inkling](https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling.md)\n- [GLM-4.5-Air vs ZAYA1-8B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-zaya1-8b.md)\n- [GLM-4.7-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling.md)\n- [GLM-4.7-Flash vs ZAYA1-8B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-zaya1-8b.md)\n- [GLM-5.3-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.md)\n- [GLM-5.3-Flash vs 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