{
  "data": {
    "a": {
      "slug": "inkling-2-small",
      "name": "Inkling 2 Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling 2 Small is Thinking Machines Lab's open-weight mixture-of-experts model, 594B total and 17B active parameters, taking text and images and returning text, with adjustable thinking effort, published in NVFP4 and MXFP8 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling-2-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json",
      "dns": "inkling-2-small.grade.anchorterminal.com",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small-MXFP8"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-11-12). 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, 393.5 GB of files for the NVFP4 checkpoint and 622.8 GB for MXFP8, which Thinking Machines puts at 500 GB and 800 GB of GPU memory. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens, $0.03 cached and $1.00 output (read 2026-11-06).",
      "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 2026-11-12).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-12"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-2-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-11-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.8,
        "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": 1524,
        "categoryRank": 78,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-12"
        },
        "negative": 0,
        "verdict": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
        "bestFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "strengths": [
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to xhigh, several tool calls a turn and a 1M-token context",
          "Two checkpoints from Thinking Machines, NVFP4 and MXFP8, under Apache 2.0 with no gate",
          "Thinking Machines' tml-renderers package renders prompts and parses tool calls for this model",
          "A training-content summary with sources, mix and an October 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference, and the card names seven more API providers"
        ],
        "weaknesses": [
          "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory",
          "No released version of vLLM, SGLang, Transformers, llama.cpp or Ollama runs it on 12 November 2026",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "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",
          "No independent benchmark results were read, so Capability is pending and the total is capped at 61"
        ],
        "agentNotes": [
          "No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image",
          "In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`",
          "Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99",
          "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026",
          "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": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.8
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "provenanceScore": 72,
        "checked": {
          "categories": {
            "interface": "2026-11-12",
            "reach": "2026-11-12",
            "risk": "2026-11-12",
            "upkeep": "2026-11-12"
          },
          "last": "2026-11-12",
          "lastMoved": "2026-11-12",
          "oldest": "2026-11-12",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, the NVFP4 checkpoint on 4 B300 GPUs. Not in an SGLang release yet,\n# so run it inside the lmsysorg/sglang:dev-inkling-2-small image:\nSGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve \\\n  --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 \\\n  --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 \\\n  --page-size 128 --grammar-backend xgrammar --enable-multimodal \\\n  --reasoning-parser inkling --tool-call-parser inkling2",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-2-Small\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling-2-small"
      },
      "sameCompany": [
        "inkling",
        "inkling-small"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "594B",
        "active": "17B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images in, a 1M-token context and thinking effort set per request.",
        "runtimes": [],
        "builds": [
          {
            "name": "Inkling-2-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 393.5,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "The main checkpoint, in the precision the model was trained in. Routed experts in NVFP4 for layers 0 to 39 and MXFP8 for layers 40 to 47, per SGLang's cookbook. Thinking Machines states at least 500 GB of GPU memory"
          },
          {
            "name": "Inkling-2-Small-MXFP8",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small-MXFP8",
            "who": "publisher",
            "precision": "mxfp8",
            "sizeGB": 622.8,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Every routed expert in MXFP8. Thinking Machines states at least 800 GB of GPU memory and recommends the NVFP4 checkpoint. It's the only checkpoint Transformers' main branch loads"
          }
        ],
        "run": "SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 --page-size 128 --grammar-backend xgrammar --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling2",
        "runBuild": "Inkling-2-Small",
        "checked": "2026-11-12",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling 2",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named as provider on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling-2-Small/commits/main",
        "securityTxt": "valid",
        "checked": "2026-11-12",
        "notes": [
          "Thinking Machines' model card page links both repositories in the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.",
          "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, 3 commits on 12 November 2026, the upload, a library tag from a merged pull request and a card update.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, read on 12 November 2026, and the model card page links a coordinated vulnerability disclosure policy.",
          "Thinking Machines' terms bar scraping the Services. The founder decided on 6 November 2026 that reading at a person's pace is fine, so six pages were read one at a time on 12 November: the acceptable use policy, the training data page and its summary for this model, the model card page, and the tml-renderers and thinking effort guides. thinkingmachines.ai's robots.txt has no rules, and tinker-docs.thinkingmachines.ai answers 404 for robots.txt."
        ],
        "score": 72
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-2-small.json",
      "live": {
        "slug": "inkling-2-small",
        "probe": {
          "target": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1",
          "method": "get",
          "lastAt": "2026-11-13T20:11:37.236512439Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 439,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 238,
          "p95ms24h": 467,
          "samples24h": 245,
          "samples30d": 1854,
          "days": [
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              "probes": 186,
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            {
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            {
              "date": "2026-11-09",
              "probes": 243,
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            {
              "date": "2026-11-10",
              "probes": 244,
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            {
              "date": "2026-11-11",
              "probes": 244,
              "ok": 244
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            {
              "date": "2026-11-12",
              "probes": 245,
              "ok": 245
            },
            {
              "date": "2026-11-13",
              "probes": 206,
              "ok": 206
            }
          ],
          "since": "2026-11-06T00:00:00Z"
        },
        "securityTxt": {
          "url": "https://thinkingmachines.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2029-07-13T07:00:00.000Z",
          "checkedAt": "2026-11-14T16:19:22.779006645Z"
        },
        "llmsTxt": {
          "url": "https://tinker-docs.thinkingmachines.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-13T15:54:36.79283015Z"
        },
        "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-2-Small/commits/main",
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            "checkedAt": "2026-11-14T19:07:35.812797752Z",
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            "checkedAt": "2026-11-13T18:32:58.088087394Z",
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            "fingerprint": "c56006412e95"
          },
          {
            "url": "https://thinkingmachines.ai/legal/privacy/",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-13T18:32:53.884197991Z",
            "changedAt": "2026-11-06T13:43:40.660240815Z",
            "fingerprint": "3c33a4a74c61"
          },
          {
            "url": "https://thinkingmachines.ai/legal/terms/",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-13T18:32:56.034092745Z",
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        "updatedAt": "2026-11-14T19:07:35.812797752Z"
      },
      "streak": {
        "days": 9,
        "from": "2026-11-06",
        "sinceWatching": true,
        "best": 9
      }
    },
    "answer": "Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach.",
    "b": {
      "slug": "laguna-m-1",
      "name": "Laguna M.1",
      "vendor": "Poolside",
      "vendorUrl": "https://poolside.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Laguna M.1 is Poolside's first-generation open-weight Mixture-of-Experts model for agentic coding, 225B total and 23B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/laguna-m-1",
      "markdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json",
      "dns": "laguna-m-1.grade.anchorterminal.com",
      "repo": "https://huggingface.co/poolside/Laguna-M.1",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-M.1"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-M.1-FP8"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-M.1-NVFP4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and both builds, although the card's metadata carries an unused gate description pointing to Poolside's privacy policy (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 451.6 GB for the BF16 files and 139.3 GB for the NVFP4 build. The card links Poolside's API for hosted use, but no inference provider is mapped on the Hub and Poolside's API docs name only Laguna S 2.1 (checked 2026-11-04).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/poolside/Laguna-M.1",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-14",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 56.7,
        "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": 1524,
        "categoryRank": 85,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "capability": 46,
          "interface": 85,
          "reach": 70,
          "risk": 55,
          "upkeep": 36
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.",
        "bestFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.",
        "strengths": [
          "Plain Apache 2.0 with no gate, account or use policy",
          "Released support in vLLM, SGLang, Transformers, llama.cpp and Ollama (through its pinned llama.cpp)",
          "Poolside's own FP8 and NVFP4 builds",
          "Tool calling and the poolside_v1 parser documented on the card, several calls a turn",
          "Thinking on or off per request, with the reasoning returned in reasoning_content"
        ],
        "weaknesses": [
          "The smallest build needs about 167 GB, more than a 128 GB machine",
          "No Ollama library or LM Studio catalogue entry, and no publisher GGUF build",
          "No change to the files since 14 July 2026 and no reply from Poolside to its one discussion",
          "No safety results and only general cautions for agent use",
          "No hosting found. No inference provider is mapped on the Hub, and Poolside's API docs name only Laguna S 2.1"
        ],
        "agentNotes": [
          "Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later",
          "Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding",
          "Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped",
          "Sampling per the card is temperature 1.0 and top_k 20",
          "The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM",
          "It doesn't fit our 128 GB reference machine at any published precision",
          "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.7
          }
        ],
        "editorialScores": {
          "capability": 46,
          "interface": 85,
          "reach": 70,
          "risk": 55,
          "upkeep": 36
        },
        "provenanceScore": 69,
        "checked": {
          "categories": {
            "capability": "2026-11-04",
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "lastMoved": "2026-11-04",
          "oldest": "2026-11-04",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install 'vllm\u003e=0.21.0'\nvllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 \\\n  --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"poolside/Laguna-M.1-NVFP4\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/laguna-m-1"
      },
      "sameCompany": [
        "laguna-s-2-1",
        "laguna-xs-2-1"
      ],
      "weights": {
        "trainedBy": "Poolside",
        "params": "225.8B total, 23B active",
        "context": 262144,
        "goodFor": "Agentic coding on a multi-GPU server, with tool calling and reasoning that turns on or off per request, under Apache 2.0.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Laguna-M.1-NVFP4",
            "url": "https://huggingface.co/poolside/Laguna-M.1-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 139.3,
            "memoryGB": 192,
            "format": "safetensors",
            "note": "For NVIDIA Blackwell GPUs"
          },
          {
            "name": "Laguna-M.1-FP8",
            "url": "https://huggingface.co/poolside/Laguna-M.1-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 238.6,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "238.6 GB summed from the file list, of which 9.5 GB is a Docker image (image/laguna-vllm-v0.19.0-overlay.tar.gz) and 229.1 GB the weights. Either way 512 GB"
          },
          {
            "name": "Laguna-M.1",
            "url": "https://huggingface.co/poolside/Laguna-M.1",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 451.6,
            "memoryGB": 1024,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ]
          }
        ],
        "run": "vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'",
        "runBuild": "Laguna-M.1-NVFP4",
        "checked": "2026-11-04",
        "minMemoryGB": 192
      },
      "family": {
        "lab": "Poolside",
        "family": "Laguna 1 (M.1)",
        "url": "https://www.anchorterminal.com/open-weights/#poolside",
        "others": [
          {
            "name": "Laguna-M.1-base",
            "url": "https://huggingface.co/poolside/Laguna-M.1-base",
            "params": "225.80B (Hub safetensors count; the name gives only the size class M)"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use; the LICENSE.md copyright line reads Poolside)",
        "domain": "poolside.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "https://poolside.ai/legal/eula",
        "privacy": "https://poolside.ai/legal/privacy",
        "statusPage": "",
        "changelog": "https://docs.poolside.ai/release-notes/models",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "The Hugging Face organisation poolside is verified, and Poolside's M.1 blog post links the repository.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "Poolside's docs keep dated model release notes, with an April 2026 entry for M.1.",
          "security.txt is PGP-signed, names a security contact at poolside.ai and expires on 1 April 2028. The domain's registration date wasn't checked."
        ],
        "score": 69
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-m-1.json",
      "live": {
        "slug": "laguna-m-1",
        "securityTxt": {
          "url": "https://poolside.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2028-04-01T12:00:00.000Z",
          "checkedAt": "2026-11-14T16:19:28.468377911Z"
        },
        "domain": {
          "domain": "poolside.ai",
          "registered": "2020-07-07",
          "source": "https://rdap.identitydigital.services/rdap/domain/poolside.ai",
          "checkedAt": "2026-11-08T14:58:52.089559761Z"
        },
        "pages": [
          {
            "url": "https://docs.poolside.ai/release-notes/models",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-14T19:00:55.580288446Z",
            "changedAt": "2026-11-13T18:17:32.636820179Z",
            "fingerprint": "387fb94f5296"
          },
          {
            "url": "https://poolside.ai/legal/privacy",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-11-14T19:10:33.088341099Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "95a56164038b"
          },
          {
            "url": "https://poolside.ai/legal/eula",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-11-14T19:10:31.07581284Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "6daf0ef509c0"
          }
        ],
        "updatedAt": "2026-11-14T19:10:33.088341099Z"
      }
    },
    "edges": [
      {
        "by": 31,
        "category": "upkeep",
        "leads": "inkling-2-small",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.",
          "b": "Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 5, the report describes sources and filtering but gives no cut-off. Last change 10, 14 July 2026, 113 days ago. Responsiveness 0, the one discussion's only reply is from someone outside the poolside organisation. Version policy 5, a first open release with nothing replaced. File health 5, generation config and template disagree on the thinking default and the FP8 build's Docker files name different image tags."
        },
        "scores": {
          "a": 67,
          "b": 36
        }
      },
      {
        "by": 30,
        "category": "reach",
        "leads": "laguna-m-1",
        "name": "Reach",
        "reasons": {
          "a": "Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.",
          "b": "Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine. Runtimes 25, released llama.cpp, Ollama (through the llama.cpp release it pins), vLLM, SGLang and Transformers run the laguna architecture. Builds 15, FP8 and NVFP4 from Poolside. Terms 15, Apache 2.0 with nothing binding added. Download 10, nothing is gated. Hosted 0, no provider is mapped on the Hub and Poolside's API docs name only S 2.1."
        },
        "scores": {
          "a": 40,
          "b": 70
        }
      },
      {
        "by": 10,
        "category": "risk",
        "leads": "inkling-2-small",
        "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, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, 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. 25 + 15 + 10 + 5 + 5 + 5 = 65.",
          "b": "File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found."
        },
        "scores": {
          "a": 65,
          "b": 55
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "Poolside",
        "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": "2026-11-12",
        "b": "2026-07-14",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "2026-07-21",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "2026-07-21",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not read yet",
        "b": "yes, with an opt-out",
        "name": "Customer content may train models"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not read yet",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not read yet",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach.",
        "question": "Which is better for AI agents, Inkling 2 Small or Laguna M.1?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 65 against 55",
          "Documentation and upkeep, 67 against 36"
        ],
        "also": null,
        "goodFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "slug": "inkling-2-small",
        "watchFor": "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory"
      },
      {
        "aheadOn": [
          "Reach, 70 against 40"
        ],
        "also": null,
        "goodFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.",
        "slug": "laguna-m-1",
        "watchFor": "The smallest build needs about 167 GB, more than a 128 GB machine"
      }
    ],
    "history": {
      "inkling-2-small": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-12",
          "delta": 6.7,
          "from": 52.1,
          "fromGrade": "D",
          "to": 58.8,
          "toGrade": "C"
        }
      ],
      "laguna-m-1": [
        {
          "causes": [
            "correction"
          ],
          "date": "2026-11-04",
          "delta": 1.2,
          "from": 55.5,
          "fromGrade": "C",
          "to": 56.7,
          "toGrade": "C"
        }
      ]
    },
    "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-inkling-2-small.json",
        "title": "Agents-A1-4B vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.json",
        "title": "Agents-A1-4B vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.json",
        "title": "Apertus v1.5 8B vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small"
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      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.json",
        "title": "Apertus v1.5 8B vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-2-small.json",
        "title": "Apodex-1.1-mini vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-2-small"
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      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.json",
        "title": "Apodex-1.1-mini vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small"
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      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling-2-small.json",
        "title": "Carbon-X vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/cola2-vs-inkling-2-small.json",
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        "json": "https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.json",
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-2-small"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling-2-small"
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        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-2-small.json",
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-2-small"
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-2-small"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.json",
        "title": "Laguna M.1 vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Laguna M.1 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.json",
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      {
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b"
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.json",
        "title": "Laguna M.1 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct.json",
        "title": "Laguna M.1 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct"
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      {
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct"
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        "title": "Laguna M.1 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct.json",
        "title": "Laguna M.1 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct.json",
        "title": "Laguna M.1 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Laguna M.1 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint.json",
        "title": "Laguna M.1 vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ripple-65b-preview.json",
        "title": "Laguna M.1 vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ripple-65b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-sensenova-loop-9b-preview.json",
        "title": "Laguna M.1 vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-sensenova-loop-9b-preview"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.json",
        "title": "Laguna M.1 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b.json",
        "title": "Laguna M.1 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.json",
        "title": "Laguna M.1 vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Laguna M.1 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Laguna M.1 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-unlimited-ocr-2.json",
        "title": "Laguna M.1 vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b.json",
        "title": "Laguna M.1 vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b.json",
        "title": "Laguna M.1 vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b.json",
        "title": "Laguna M.1 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 30,
        "edge": "laguna-m-1",
        "inkling-2-small": 40,
        "key": "reach",
        "laguna-m-1": 70,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 10,
        "edge": "inkling-2-small",
        "inkling-2-small": 65,
        "key": "risk",
        "laguna-m-1": 55,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "inkling-2-small": 85,
        "key": "interface",
        "laguna-m-1": 85,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 31,
        "edge": "inkling-2-small",
        "inkling-2-small": 67,
        "key": "upkeep",
        "laguna-m-1": 36,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "inkling-2-small": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
      "laguna-m-1": "A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published."
    }
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  "links": {
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    "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
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    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1.min.md"
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  "markdown": "Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach. Both do open-weight models you run yourself.\n\n- Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json\n- Laguna M.1: grade C, 56.7/100, rank #113 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-m-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-m-1.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 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Inkling 2 Small (C)\n\nGood for: Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.\n\nAhead on:\n- Risk, 65 against 55\n- Documentation and upkeep, 67 against 36\n\nWatch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory\n\n### Laguna M.1 (C)\n\nGood for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.\n\nAhead on:\n- Reach, 70 against 40\n\nWatch for: The smallest build needs about 167 GB, more than a 128 GB machine\n\n\n## Why the edge\n\n### Documentation and upkeep: Inkling 2 Small +31\n\n- Inkling 2 Small (67): Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.\n- Laguna M.1 (36): Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 5, the report describes sources and filtering but gives no cut-off. Last change 10, 14 July 2026, 113 days ago. Responsiveness 0, the one discussion's only reply is from someone outside the poolside organisation. Version policy 5, a first open release with nothing replaced. File health 5, generation config and template disagree on the thinking default and the FP8 build's Docker files name different image tags.\n\n### Reach: Laguna M.1 +30\n\n- Inkling 2 Small (40): Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.\n- Laguna M.1 (70): Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine. Runtimes 25, released llama.cpp, Ollama (through the llama.cpp release it pins), vLLM, SGLang and Transformers run the laguna architecture. Builds 15, FP8 and NVFP4 from Poolside. Terms 15, Apache 2.0 with nothing binding added. Download 10, nothing is gated. Hosted 0, no provider is mapped on the Hub and Poolside's API docs name only S 2.1.\n\n### Risk: Inkling 2 Small +10\n\n- Inkling 2 Small (65): 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, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, 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. 25 + 15 + 10 + 5 + 5 + 5 = 65.\n- Laguna M.1 (55): File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.\n\n## Score by category\n\n| Category | Weight | Inkling 2 Small | Laguna M.1 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 40 | 70 | Laguna M.1 +30 |\n| Risk | 20% (20 this run) | 65 | 55 | Inkling 2 Small +10 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 67 | 36 | Inkling 2 Small +31 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **58.8 · C** | **56.7 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling 2 Small | Laguna M.1 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | Poolside |\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 | 2026-11-12 | 2026-07-14 |\n| Terms last updated | no document linked | 2026-07-21 |\n| Privacy policy last updated | no document linked | 2026-07-21 |\n| Customer content may train models | not read yet | yes, with an opt-out |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | yes |\n| Arbitration or class-action waiver | not read yet | yes |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n### Laguna M.1\n\n- +1.2 on 4 November 2026: correction\n\n## Verdicts\n\n**Inkling 2 Small.** Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.\n\n**Laguna M.1.** A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.\n\n## Before you call either\n\n### Inkling 2 Small\n\n1. No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image\n2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`\n3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet\n4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99\n5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part\n8. Use guided decoding or validate JSON yourself, since structured output isn't documented\n9. Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026\n10. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### Laguna M.1\n\n1. Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later\n2. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding\n3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n4. Sampling per the card is temperature 1.0 and top_k 20\n5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM\n6. It doesn't fit our 128 GB reference machine at any published precision\n7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, Inkling 2 Small or Laguna M.1?\n\nInkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-m-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-2-small\", \"b\": \"laguna-m-1\"}`. From a terminal: `anchor compare inkling-2-small laguna-m-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json and https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json\n\n## Other comparisons with Inkling 2 Small or Laguna M.1\n\n- [Agents-A1-4B vs Inkling 2 Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.md)\n- [Agents-A1-4B vs Laguna M.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.md)\n- [Apertus v1.5 8B vs Inkling 2 Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.md)\n- [Apertus v1.5 8B vs Laguna M.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.md)\n- [Apodex-1.1-mini vs Inkling 2 Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-2-small.md)\n- [Apodex-1.1-mini vs Laguna M.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.md)\n- [Arete-27B vs Inkling 2 Small](https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small.md)\n- [Arete-27B vs Laguna M.1](https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1.md)\n- [BigBang-v1 vs Inkling 2 Small](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.md)\n- [BigBang-v1 vs Laguna M.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.md)\n- [Carbon-X vs Inkling 2 Small](https://www.anchorterminal.com/compare/carbon-x-vs-inkling-2-small.md)\n- [Carbon-X vs Laguna M.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.md)\n- [Cola2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/cola2-vs-inkling-2-small.md)\n- [Cola2 vs Laguna M.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1.md)\n- [Cosmos-Reason2-2B vs Inkling 2 Small](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-2-small.md)\n- [Cosmos-Reason2-2B vs Laguna M.1](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.md)\n- [Darwin-36B-Opus vs Inkling 2 Small](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-2-small.md)\n- [Darwin-36B-Opus vs Laguna M.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.md)\n- [DeepSeek-V3.2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-2-small.md)\n- [DeepSeek-V3.2 vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.md)\n- [DeepSeek V4.1 Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-2-small.md)\n- [DeepSeek V4.1 Flash vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1.md)\n- [DeepSeek-V4-Flash-0731 vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.md)\n- [DeepSeek-V4-Flash-0731 vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-m-1.md)\n- [Devstral Small 2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling-2-small.md)\n- [Devstral Small 2 vs Laguna M.1](https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1.md)\n- [DiffusionGemma 26B A4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-2-small.md)\n- [DiffusionGemma 26B A4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-m-1.md)\n- [EXAONE 4.5 33B vs Inkling 2 Small](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-2-small.md)\n- [EXAONE 4.5 33B vs Laguna M.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.md)\n- [Gemma 4 12B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-2-small.md)\n- [Gemma 4 12B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-m-1.md)\n- [Gemma 4 26B A4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.md)\n- [Gemma 4 26B A4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-m-1.md)\n- [Gemma 4 31B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-2-small.md)\n- [Gemma 4 31B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-m-1.md)\n- [Gemma 4 E2B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-2-small.md)\n- [Gemma 4 E2B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-m-1.md)\n- [Gemma 4 E4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-2-small.md)\n- [Gemma 4 E4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-m-1.md)\n- [GLM-4.5-Air vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-2-small.md)\n- [GLM-4.5-Air vs Laguna M.1](https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-m-1.md)\n- [GLM-4.7-Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-2-small.md)\n- [GLM-4.7-Flash vs Laguna M.1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-m-1.md)\n- [GLM-5.3-Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.md)\n- [GLM-5.3-Flash vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-m-1.md)\n- [GLM-5.3 vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-2-small.md)\n- [GLM-5.3 vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.md)\n- [gpt-oss-120b vs Inkling 2 Small](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.md)\n- [gpt-oss-120b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-m-1.md)\n- [gpt-oss-20b vs Inkling 2 Small](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-2-small.md)\n- [gpt-oss-20b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-m-1.md)\n- [Granite 4.2 30B vs Inkling 2 Small](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-inkling-2-small.md)\n- [Granite 4.2 30B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-m-1.md)\n- [Granite 4.2 3B vs Inkling 2 Small](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling-2-small.md)\n- [Granite 4.2 3B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-m-1.md)\n- [Granite 4.2 8B vs Inkling 2 Small](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling-2-small.md)\n- [Granite 4.2 8B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-m-1.md)\n- [Hy-Memory-30B-A3B vs Inkling 2 Small](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling-2-small.md)\n- [Hy-Memory-30B-A3B vs Laguna M.1](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-m-1.md)\n- [Hy3 vs Inkling 2 Small](https://www.anchorterminal.com/compare/hy3-vs-inkling-2-small.md)\n- [Hy3 vs Laguna M.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1.md)\n- [Inkling 2 Small vs Inkling-Small](https://www.anchorterminal.com/compare/inkling-2-small-vs-inkling-small.md)\n- [Inkling 2 Small vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/inkling-2-small-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Inkling 2 Small vs Kimi K3](https://www.anchorterminal.com/compare/inkling-2-small-vs-kimi-k3.md)\n- [Inkling 2 Small vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/inkling-2-small-vs-kimi-k3-1-pro.md)\n- [Inkling 2 Small vs Kolibri-1](https://www.anchorterminal.com/compare/inkling-2-small-vs-kolibri-1.md)\n- [Inkling 2 Small vs Kronos](https://www.anchorterminal.com/compare/inkling-2-small-vs-kronos.md)\n- [Inkling 2 Small vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-s-2-1.md)\n- [Inkling 2 Small vs Laguna XS 2.1](https://www.anchorterminal.com/compare/inkling-2-small-vs-laguna-xs-2-1.md)\n- [Inkling 2 Small vs LBS-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lbs-27b.md)\n- [Inkling 2 Small vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm2-5-2-6b.md)\n- [Inkling 2 Small vs LFM3-1.7B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-1-7b.md)\n- [Inkling 2 Small vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-audio-2b.md)\n- [Inkling 2 Small vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-omni-2b.md)\n- [Inkling 2 Small vs LFM3-VL-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-lfm3-vl-2b.md)\n- [Inkling 2 Small vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/inkling-2-small-vs-ling-3-0-tiny.md)\n- [Inkling 2 Small vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/inkling-2-small-vs-ling-3-1-flash-1019.md)\n- [Inkling 2 Small vs LongCat-2.5](https://www.anchorterminal.com/compare/inkling-2-small-vs-longcat-2-5.md)\n- [Inkling 2 Small vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Inkling 2 Small vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-flash-rl.md)\n- [Inkling 2 Small vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-o-4-5.md)\n- [Inkling 2 Small vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-v-4-7-1b.md)\n- [Inkling 2 Small vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-v-4-7-35b-a3b.md)\n- [Inkling 2 Small vs MiniCPM5-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm5-2b.md)\n- [Inkling 2 Small vs MiniMax-M2.5](https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.md)\n- [Inkling 2 Small vs MiniMax-M2.7](https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-7.md)\n- [Inkling 2 Small vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m3-1-flash.md)\n- [Inkling 2 Small vs Mistral Large 4](https://www.anchorterminal.com/compare/inkling-2-small-vs-mistral-large-4.md)\n- [Inkling 2 Small vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-glimmer-30b.md)\n- [Inkling 2 Small vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-2-3b.md)\n- [Inkling 2 Small vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-3-33b.md)\n- [Inkling 2 Small vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [Inkling 2 Small vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Inkling 2 Small vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b.md)\n- [Inkling 2 Small vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-4b.md)\n- [Inkling 2 Small vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Inkling 2 Small vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.md)\n- [Inkling 2 Small vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-ultra-550b-a55b.md)\n- [Inkling 2 Small vs North Mini Code 1.0](https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0.md)\n- [Inkling 2 Small vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0.md)\n- [Inkling 2 Small vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think.md)\n- [Inkling 2 Small vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b.md)\n- [Inkling 2 Small vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b.md)\n- [Inkling 2 Small vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-397b.md)\n- [Inkling 2 Small vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-9b.md)\n- [Inkling 2 Small vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/inkling-2-small-vs-otel-2-0-llm-31b-it.md)\n- [Inkling 2 Small vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b.md)\n- [Inkling 2 Small vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Inkling 2 Small vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.md)\n- [Inkling 2 Small vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.md)\n- [Inkling 2 Small vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b.md)\n- [Inkling 2 Small vs Qwen3.5-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b.md)\n- [Inkling 2 Small vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b.md)\n- [Inkling 2 Small vs Qwen3.5-4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b.md)\n- [Inkling 2 Small vs Qwen3.5-9B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b.md)\n- [Inkling 2 Small vs Qwen3.6-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.md)\n- [Inkling 2 Small vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.md)\n- [Inkling 2 Small vs Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.md)\n- [Inkling 2 Small vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.md)\n- [Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Inkling 2 Small vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next.md)\n- [Inkling 2 Small vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Inkling 2 Small vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct.md)\n- [Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Inkling 2 Small vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct.md)\n- [Inkling 2 Small vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct.md)\n- [Inkling 2 Small vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.md)\n- [Inkling 2 Small vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2.md)\n- [Inkling 2 Small vs Recursive Flint](https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint.md)\n- [Inkling 2 Small vs Ripple-65B 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    "description": "Inkling 2 Small scores 58.8 (C) to Laguna M.1's 56.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
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    "title": "Inkling 2 Small vs Laguna M.1 for AI agents in 2026: scores and prices",
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