{
  "data": {
    "a": {
      "slug": "inkling-small",
      "name": "Inkling-Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling-Small is Thinking Machines Lab's open-weight mixture-of-experts model, 276B total and 12B 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-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-small.json",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-Small-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, 531.9 GB for the BF16 files and 170.8 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens and $1.20 per million output tokens (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "audio",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-31",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 66.5,
        "grade": "B",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 11,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 63,
          "interface": 85,
          "reach": 55,
          "risk": 70,
          "upkeep": 82
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.",
        "bestFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.",
        "strengths": [
          "Thinking Machines answered 8 of the 9 questions in its discussions",
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to the maximum, several tool calls a turn and a 1M-token context",
          "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers",
          "A training-content summary with sources, mix and a July 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference"
        ],
        "weaknesses": [
          "The smallest build Thinking Machines publishes needs about 205 GB",
          "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": [
          "Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4",
          "Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself",
          "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 and SGLang's cookbook list xhigh",
          "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 and audio 16 kHz WAV under two minutes, per the card",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "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": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 66.5
          }
        ],
        "editorialScores": {
          "capability": 63,
          "interface": 85,
          "reach": 55,
          "risk": 70,
          "upkeep": 82
        },
        "provenanceScore": 67,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, NVFP4 on 8 Blackwell GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 \\\n  --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-Small-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-small"
      },
      "sameCompany": [
        "inkling"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "276B",
        "active": "12B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images and audio in, and thinking effort set per request.",
        "runtimes": [
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Inkling-Small-NVFP4",
            "url": "https://huggingface.co/thinkingmachines/Inkling-Small-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 170.8,
            "memoryGB": 256,
            "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-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-Small",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 531.9,
            "memoryGB": 1024,
            "format": "safetensors"
          }
        ],
        "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling",
        "runBuild": "Inkling-Small-NVFP4",
        "checked": "2026-10-21",
        "minMemoryGB": 256
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines",
        "others": [
          {
            "name": "Inkling",
            "url": "https://huggingface.co/thinkingmachines/Inkling",
            "params": "952.38B (Hub safetensors count; the name states none)",
            "listing": "https://www.anchorterminal.com/tools/inkling"
          }
        ],
        "unrestrictedCopies": 3
      },
      "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-Small/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "Thinking Machines' model card page and launch post link 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, 12 commits from 27 to 31 July 2026, an upload, card updates and community evaluation results.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, and the site publishes a coordinated vulnerability disclosure policy that leaves model safety to a separate incident contact."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-small.json"
    },
    "answer": "Inkling-Small scores 66.5 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability and reach.",
    "b": {
      "slug": "minimax-m2-5",
      "name": "MiniMax-M2.5",
      "vendor": "MiniMax",
      "vendorUrl": "https://www.minimax.io",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniMax-M2.5 is MiniMax's open-weight mixture-of-experts model for coding and agent work, about 229B parameters in FP8 with a 196,608-token context and thinking always on, published on Hugging Face on 12 February 2026.",
      "url": "https://www.anchorterminal.com/tools/minimax-m2-5",
      "markdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json",
      "repo": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5",
      "license": "MiniMax Model License (model) and modified MIT (code)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "MiniMaxAI/MiniMax-M2.5"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included and royalty-free, under the MiniMax Model License for the weights and a modified MIT licence for the code, both with attribution duties and a Prohibited Uses Policy for the model. Running it yourself costs the hardware, 230.2 GB of FP8 files. MiniMax's API closed M2.5 to new users on 19 October 2026 and retires it on 18 November 2026 (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "coding",
        "custom-licence",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-02-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 57.5,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 57,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 73,
          "interface": 75,
          "reach": 65,
          "risk": 30,
          "upkeep": 22
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.",
        "bestFor": "Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy",
        "strengths": [
          "Runs in released vLLM, SGLang, llama.cpp, Transformers and LM Studio",
          "Tool-call format documented by MiniMax with named vLLM and SGLang parsers and a parsing function",
          "Several tool calls in one block, and 196,608 tokens of context",
          "Safetensors only, in the publisher's organisation with a SHA-256 for every shard",
          "No gate or account, and served by two inference providers on Hugging Face"
        ],
        "weaknesses": [
          "230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine",
          "Thinking is always on, with no documented way to turn it off or budget it",
          "The card says modified MIT and links to a deleted file, while the licence in the repository adds a Prohibited Uses Policy and termination for breach",
          "No safety evaluation, agent guidance or security contact",
          "No MiniMax reply in discussions since April 2026, and the card leaves out limitations, architecture, parameters and a cut-off"
        ],
        "agentNotes": [
          "Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think",
          "In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code",
          "MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache",
          "On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory",
          "Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends",
          "Budget output tokens for thinking on every turn, since the template always opens a think block",
          "Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy",
          "Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 1.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 57.5
          }
        ],
        "editorialScores": {
          "capability": 73,
          "interface": 75,
          "reach": 65,
          "risk": 30,
          "upkeep": 22
        },
        "provenanceScore": 55,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# MiniMax's vLLM guide, 4 GPUs\nuv pip install vllm --torch-backend=auto\nSAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code \\\n  --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 \\\n  --reasoning-parser minimax_m2_append_think",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"MiniMaxAI/MiniMax-M2.5\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 1.0, \"top_p\": 0.95, \"top_k\": 40}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minimax-m2-5"
      },
      "sameCompany": [
        "minimax-api",
        "minimax-video",
        "minimax-voice-cloning",
        "minimax-code",
        "minimax-m2-7"
      ],
      "weights": {
        "trainedBy": "MiniMax",
        "params": "228.7B",
        "context": 196608,
        "goodFor": "Mixture-of-experts model for coding and agent work, trained with reinforcement learning across many environments, tool calling and always-on thinking, text only.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiniMax-M2.5",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 230.1,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "Native FP8; the only build MiniMax publishes"
          }
        ],
        "run": "SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think",
        "runBuild": "MiniMax-M2.5",
        "checked": "2026-10-21",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "MiniMax",
        "family": "MiniMax-M2",
        "url": "https://www.anchorterminal.com/open-weights/#minimax",
        "others": [
          {
            "name": "MiniMax-M2",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2",
            "params": "230B total, 10B active"
          },
          {
            "name": "MiniMax-M2.1",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.1",
            "params": "230B total, 10B active (Hub count; card doesn't restate)"
          },
          {
            "name": "MiniMax-M2.7",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.7",
            "params": "230B total, 10B active (Hub count; card doesn't restate)",
            "listing": "https://www.anchorterminal.com/tools/minimax-m2-7"
          }
        ],
        "olderCount": 7,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "MiniMax AI (named in the licences; MiniMax's platform terms name Nanonoble Pte. Ltd., Singapore)",
        "domain": "minimax.io",
        "domainRegistered": "2021-03-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The MiniMax Model License and the MIT code licence name MiniMax AI. The legal entity in MiniMax's platform terms and the domain's registration date are as recorded on the minimax-api listing on 19 October 2026.",
          "Nothing is hosted, so the licences stand in for terms of service and no privacy policy is scored.",
          "No changelog. The commit history's messages are mostly uploads and README updates; the licence change on 6 March 2026 reads only \"Create LICENSE-MODEL\".",
          "www.minimax.io/.well-known/security.txt redirects to the home page on 21 October 2026, so there is no security.txt.",
          "MiniMax's site (www.minimax.io/models/text) links to huggingface.co/MiniMaxAI/MiniMax-M2.5, so the repository is the publisher's own."
        ],
        "score": 55
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "MiniMax",
        "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": "MiniMax Model License (model) and modified MIT (code)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-07-31",
        "b": "2026-02-12",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "3.5/5 (4)",
        "b": "1.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling-Small scores 66.5 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability and reach.",
        "question": "Which is better for AI agents, Inkling-Small or MiniMax-M2.5?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 70 against 30",
          "Agent interface, 85 against 75",
          "Documentation and upkeep, 82 against 22"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 1.8 out of 5"
        ],
        "goodFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.",
        "slug": "inkling-small",
        "watchFor": "The smallest build Thinking Machines publishes needs about 205 GB"
      },
      {
        "aheadOn": [
          "Capability, 73 against 63",
          "Reach, 65 against 55"
        ],
        "also": null,
        "goodFor": "Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy",
        "slug": "minimax-m2-5",
        "watchFor": "230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.json",
        "title": "Agents-A1-4B vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5.json",
        "title": "Agents-A1-4B vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.json",
        "title": "Apertus v1.5 8B vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5.json",
        "title": "Apertus v1.5 8B vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.json",
        "title": "Apodex-1.1-mini vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5.json",
        "title": "Apodex-1.1-mini vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-small.json",
        "title": "BigBang-v1 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-5.json",
        "title": "BigBang-v1 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small.json",
        "title": "Cosmos-Reason2-2B vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5.json",
        "title": "Cosmos-Reason2-2B vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small.json",
        "title": "Darwin-36B-Opus vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-5.json",
        "title": "Darwin-36B-Opus vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small.json",
        "title": "DeepSeek-V3.2 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5.json",
        "title": "DeepSeek-V3.2 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-small.json",
        "title": "DeepSeek V4.1 Flash vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-5.json",
        "title": "DeepSeek V4.1 Flash vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small.json",
        "title": "DeepSeek-V4-Flash-0731 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-5.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-small.json",
        "title": "DiffusionGemma 26B A4B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-5.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-small.json",
        "title": "Gemma 4 12B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-5.json",
        "title": "Gemma 4 12B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-small.json",
        "title": "Gemma 4 26B A4B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-5.json",
        "title": "Gemma 4 26B A4B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-small.json",
        "title": "Gemma 4 31B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-5.json",
        "title": "Gemma 4 31B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-small.json",
        "title": "Gemma 4 E2B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-5.json",
        "title": "Gemma 4 E2B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-small.json",
        "title": "Gemma 4 E4B IT vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-5.json",
        "title": "Gemma 4 E4B IT vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-small.json",
        "title": "GLM-4.5-Air vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-5.json",
        "title": "GLM-4.5-Air vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-small.json",
        "title": "GLM-4.7-Flash vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-5.json",
        "title": "GLM-4.7-Flash vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small.json",
        "title": "GLM-5.3-Flash vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5.json",
        "title": "GLM-5.3-Flash vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.json",
        "title": "GLM-5.3 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.json",
        "title": "GLM-5.3 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small.json",
        "title": "gpt-oss-120b vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5.json",
        "title": "gpt-oss-120b vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-small.json",
        "title": "gpt-oss-20b vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-5.json",
        "title": "gpt-oss-20b vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling-small.json",
        "title": "Granite 4.2 3B vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-5.json",
        "title": "Granite 4.2 3B vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-inkling-small.json",
        "title": "Hy3 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.json",
        "title": "Hy3 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Inkling-Small vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-internvl3-5-gpt-oss-20b-a4b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3.json",
        "title": "Inkling-Small vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kolibri-1.json",
        "title": "Inkling-Small vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-kolibri-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1.json",
        "title": "Inkling-Small vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.json",
        "title": "Inkling-Small vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1.json",
        "title": "Inkling-Small vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm2-5-2-6b.json",
        "title": "Inkling-Small vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm2-5-2-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-0-tiny.json",
        "title": "Inkling-Small vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-0-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Inkling-Small vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5.json",
        "title": "Inkling-Small vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json",
        "title": "Inkling-Small vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7.json",
        "title": "Inkling-Small vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b.json",
        "title": "Inkling-Small vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Inkling-Small vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Inkling-Small vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-4b.json",
        "title": "Inkling-Small vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Inkling-Small vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.json",
        "title": "Inkling-Small vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Inkling-Small vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.json",
        "title": "Inkling-Small vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.json",
        "title": "Inkling-Small vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-35b-a3b.json",
        "title": "Inkling-Small vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-397b.json",
        "title": "Inkling-Small vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-9b.json",
        "title": "Inkling-Small vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Inkling-Small vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.json",
        "title": "Inkling-Small vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-0-8b.json",
        "title": "Inkling-Small vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-0-8b"
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-2b"
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        "title": "Inkling-Small vs Qwen3.5-397B-A17B",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-9b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b"
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        "title": "Inkling-Small vs Qwen3.6-35B-A3B",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b.json",
        "title": "Inkling-Small vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct.json",
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      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-spark-x2-6-4b.json",
        "title": "MiniMax-M2.5 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-27b.json",
        "title": "MiniMax-M2.5 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "MiniMax-M2.5 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-thinkingcap-qwen3-8-27b.json",
        "title": "MiniMax-M2.5 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "by": 10,
        "edge": "minimax-m2-5",
        "inkling-small": 63,
        "key": "capability",
        "minimax-m2-5": 73,
        "name": "Capability",
        "weight": 35
      },
      {
        "by": 10,
        "edge": "minimax-m2-5",
        "inkling-small": 55,
        "key": "reach",
        "minimax-m2-5": 65,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 40,
        "edge": "inkling-small",
        "inkling-small": 70,
        "key": "risk",
        "minimax-m2-5": 30,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 10,
        "edge": "inkling-small",
        "inkling-small": 85,
        "key": "interface",
        "minimax-m2-5": 75,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 60,
        "edge": "inkling-small",
        "inkling-small": 82,
        "key": "upkeep",
        "minimax-m2-5": 22,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Inkling-Small scores 66.5 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability and reach. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "inkling-small": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.",
      "minimax-m2-5": "MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5",
    "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.min.md"
  },
  "markdown": "Inkling-Small scores 66.5 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability and reach. Both do open-weight models you run yourself.\n\n- Inkling-Small: grade B, 66.5/100, rank #14 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-small.json\n- MiniMax-M2.5: grade C, 57.5/100, rank #71 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Inkling-Small (B)\n\nGood for: Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.\n\nAhead on:\n- Risk, 70 against 30\n- Agent interface, 85 against 75\n- Documentation and upkeep, 82 against 22\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 1.8 out of 5\n\nWatch for: The smallest build Thinking Machines publishes needs about 205 GB\n\n### MiniMax-M2.5 (C)\n\nGood for: Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy\n\nAhead on:\n- Capability, 73 against 63\n- Reach, 65 against 55\n\nWatch for: 230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine\n\n\n## Score by category\n\n| Category | Weight | Inkling-Small | MiniMax-M2.5 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 63 | 73 | MiniMax-M2.5 +10 |\n| Reach | 25% (25 this run) | 55 | 65 | MiniMax-M2.5 +10 |\n| Risk | 20% (20 this run) | 70 | 30 | Inkling-Small +40 |\n| Agent interface | 10% (10 this run) | 85 | 75 | Inkling-Small +10 |\n| Documentation and upkeep | 10% (10 this run) | 82 | 22 | Inkling-Small +60 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **66.5 · B** | **57.5 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling-Small | MiniMax-M2.5 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | MiniMax |\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 | MiniMax Model License (model) and modified MIT (code) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-31 | 2026-02-12 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 3.5/5 (4) | 1.8/5 (4) |\n\n## Verdicts\n\n**Inkling-Small.** A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n**MiniMax-M2.5.** MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.\n\n## Before you call either\n\n### Inkling-Small\n\n1. Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4\n2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself\n3. 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 and SGLang's cookbook list xhigh\n4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card\n7. Use guided decoding or validate JSON yourself, since structured output isn't documented\n8. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### MiniMax-M2.5\n\n1. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think\n2. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code\n3. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache\n4. On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory\n5. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends\n6. Budget output tokens for thinking on every turn, since the template always opens a think block\n7. Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy\n8. Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026\n\n## Questions\n\n### Which is better for AI agents, Inkling-Small or MiniMax-M2.5?\n\nInkling-Small scores 66.5 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability and reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-small\", \"b\": \"minimax-m2-5\"}`. From a terminal: `anchor compare inkling-small minimax-m2-5`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-small.json and https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json\n\n## Other comparisons with Inkling-Small or MiniMax-M2.5\n\n- [Agents-A1-4B vs Inkling-Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.md)\n- [Agents-A1-4B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5.md)\n- [Apertus v1.5 8B vs Inkling-Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.md)\n- [Apertus v1.5 8B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5.md)\n- [Apodex-1.1-mini vs Inkling-Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.md)\n- [Apodex-1.1-mini vs MiniMax-M2.5](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5.md)\n- [BigBang-v1 vs 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    "section": "tools",
    "title": "Inkling-Small vs MiniMax-M2.5 for AI agents in 2026: scores and prices",
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    "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5"
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