{ "data": { "a": { "slug": "gpt-oss-120b", "name": "gpt-oss-120b", "vendor": "OpenAI", "vendorUrl": "https://openai.com", "kind": "weights", "category": "open-weights", "summary": "gpt-oss-120b is OpenAI's open-weight mixture-of-experts reasoning model, 116.8B parameters with 5.1B active and a 131,072-token context, published on Hugging Face in MXFP4 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/gpt-oss-120b", "markdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json", "dns": "gpt-oss-120b.grade.anchorterminal.com", "repo": "https://huggingface.co/openai/gpt-oss-120b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "openai/gpt-oss-120b" }, { "registry": "pypi", "name": "gpt-oss" }, { "registry": "pypi", "name": "openai-harmony" }, { "registry": "ollama", "name": "gpt-oss:120b" } ], "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, under Apache 2.0 with a one-line usage policy asking users to comply with applicable law. OpenAI's API page for the model shows no price and rate limits of 0 at every tier. Running it yourself costs the hardware, 65.2 GB for the MXFP4 files and 65 GB for Ollama's gpt-oss:120b build (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/openai/gpt-oss-120b", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "apache-2.0", "safetensors", "mxfp4", "self-hosted" ], "lastRelease": "2025-08-26", "graded": true, "anchor": { "graded": true, "score": 70.2, "grade": "BB", "agentReady": true, "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": 4, "methodology": "0.8", "run": "2026-10-01", "scores": { "capability": 54, "interface": 90, "reach": 75, "risk": 95, "upkeep": 45 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-01" }, "negative": 0, "verdict": "A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.", "bestFor": "Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support", "strengths": [ "Runs in Transformers, vLLM, SGLang, llama.cpp and Ollama, with LM Studio linked from the card", "Apache 2.0, no gate, and 11 inference providers serve it for agents without the hardware", "Safetensors only, a trained instruction hierarchy and an outside biosecurity evaluation", "Harmony tool format, JSON Schema output and three reasoning levels documented by OpenAI" ], "weaknesses": [ "Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision", "One tool call at a time", "No OpenAI reply in the last 40 discussions, including open template and tokenizer reports", "No change to the files since August 2025 or to the model code since November 2025", "Reasoning can be lowered but not turned off" ], "agentNotes": [ "Start it with `ollama run gpt-oss:120b` on the reference machine, the build that fits", "On the Strix Halo machine raise the GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is below the 78 GB it needs", "With vLLM use `vllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice` per vLLM's recipe, or parse raw output with openai-harmony", "Always use the harmony format through the chat template or openai-harmony, the card says it won't work correctly otherwise", "Set `Reasoning: low` in the system message for short tasks, medium is the default", "Pass the reasoning back after a tool call until the final answer, and keep the analysis channel away from end users", "Expect one tool call per turn and loop, don't wait for parallel calls" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "BB", "methodology": "0.8", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 70.2 } ], "editorialScores": { "capability": 54, "interface": 90, "reach": 75, "risk": 95, "upkeep": 45 }, "provenanceScore": 89, "checked": { "categories": { "capability": "2026-11-01", "interface": "2026-11-01", "reach": "2026-11-01", "risk": "2026-11-01", "upkeep": "2026-11-01" }, "last": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run gpt-oss:120b\n# or, with vLLM's recipe:\nvllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice\n# or, with llama.cpp and llama.cpp's own GGUF:\nllama-server -hf ggml-org/gpt-oss-120b-GGUF:MXFP4 --jinja", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"gpt-oss:120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/gpt-oss-120b" }, "sameCompany": [ "openai-api", "openai-embeddings", "openai-guardrails", "openai-moderation", "openai-image-api", "openai-sora", "openai-speech-to-text", "gpt-live", "openai-realtime", "openai-agents-sdk", "openai-decisions-api", "openai-agents-api", "openai-codex", "openai-dots", "gpt-oss-20b" ], "weights": { "trainedBy": "OpenAI", "params": "116.83B", "active": "5.13B", "context": 131072, "goodFor": "Larger text reasoning model for agents and coding, with function calling, built-in browser and Python tools and three reasoning levels, in the harmony format.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "gpt-oss-120b", "url": "https://huggingface.co/openai/gpt-oss-120b", "who": "publisher", "precision": "mxfp4", "sizeGB": 65.2, "memoryGB": 96, "format": "safetensors", "note": "MoE weights in MXFP4, the rest BF16. original/ and metal/ duplicate the weights. vLLM's gpt-oss recipe doesn't list gfx1151" }, { "name": "ollama gpt-oss:120b", "url": "https://ollama.com/library/gpt-oss:120b", "who": "ollama", "precision": "mxfp4", "sizeGB": 65, "memoryGB": 96, "format": "ollama", "runsOn": [ "Ollama" ], "note": "OpenAI's MXFP4 weights; the card links it. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant" }, { "name": "ggml-org gpt-oss-120b-GGUF (MXFP4)", "url": "https://huggingface.co/ggml-org/gpt-oss-120b-GGUF", "who": "llama.cpp", "precision": "mxfp4", "sizeGB": 63.39, "memoryGB": 96, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From ggml-org, the llama.cpp project's organisation. 63.39 GB of MXFP4 weights, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it yet" } ], "run": "ollama run gpt-oss:120b", "runBuild": "ollama gpt-oss:120b", "checked": "2026-10-21", "minMemoryGB": 96 }, "family": { "lab": "OpenAI", "family": "gpt-oss", "url": "https://www.anchorterminal.com/open-weights/#openai", "others": [ { "name": "gpt-oss-20b", "url": "https://huggingface.co/openai/gpt-oss-20b", "params": "21B total, 3.6B active (MoE)", "listing": "https://www.anchorterminal.com/tools/gpt-oss-20b" }, { "name": "gpt-oss-safeguard-120b", "url": "https://huggingface.co/openai/gpt-oss-safeguard-120b", "params": "117B total, 5.1B active (MoE)" }, { "name": "gpt-oss-safeguard-20b", "url": "https://huggingface.co/openai/gpt-oss-safeguard-20b", "params": "21B total, 3.6B active (MoE)" } ], "olderCount": 6, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "OpenAI (named as publisher on the card; the openai-api listing's terms name OpenAI OpCo, LLC)", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, before OpenAI existed.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/openai/gpt-oss/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "The LICENSE file is Apache 2.0 with the template's placeholder copyright line, so the legal entity is the one OpenAI's own terms name, read for the openai-api listing.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "The changelog is the gpt-oss GitHub repository's commit history and tags (v0.0.1 to v0.0.9); the Hugging Face repository's commits stop on 26 August 2025.", "openai.com/.well-known/security.txt answered on 21 October 2026 with a Bugcrowd contact, an acknowledgements page and a coordinated vulnerability disclosure policy. It has no Expires line, which RFC 9116 requires." ], "score": 89 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt-oss-120b.json", "live": { "slug": "gpt-oss-120b", "versions": [ { "registry": "pypi", "name": "gpt-oss", "version": "0.0.9", "released": "2026-01-13", "seenAt": "2026-11-15T11:18:32.905887052Z" }, { "registry": "pypi", "name": "openai-harmony", "version": "0.0.8", "released": "2025-11-05", "seenAt": "2026-11-15T11:18:33.105987839Z" } ], "pypiWeekly": 8495, "securityTxt": { "url": "https://openai.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-14T16:17:34.617239149Z" }, "domain": { "domain": "openai.com", "registered": "2007-01-19", "source": "https://rdap.verisign.com/com/v1/domain/openai.com", "checkedAt": "2026-11-08T14:52:04.4095079Z" }, "updatedAt": "2026-11-15T11:18:33.105987839Z" } }, "answer": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on documentation and upkeep.", "b": { "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": [ { "date": "2026-11-06", "probes": 186, "ok": 186 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 243, "ok": 243 }, { "date": "2026-11-10", "probes": 244, "ok": 244 }, { "date": "2026-11-11", "probes": 244, "ok": 244 }, { "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", "kind": "changelog", "status": 200, "checkedAt": "2026-11-14T19:07:35.812797752Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "39971da7a686" }, { "url": "https://tinker-docs.thinkingmachines.ai/changelog/", "kind": "changelog", "status": 200, "checkedAt": "2026-11-13T18:32:58.088087394Z", "changedAt": "2026-11-13T18:32:58.088087394Z", "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", "changedAt": "2026-11-06T13:43:42.918165055Z", "fingerprint": "08c6ceca5dbb" } ], "updatedAt": "2026-11-14T19:07:35.812797752Z" }, "streak": { "days": 9, "from": "2026-11-06", "sinceWatching": true, "best": 9 } }, "edges": [ { "by": 35, "category": "reach", "leads": "gpt-oss-120b", "name": "Reach", "reasons": { "a": "Memory earns 10, because the smallest 4-bit build, Ollama's 65 GB gpt-oss:120b, needs about 78 GB with the fifth added, which fits the reference machine but not 64 GB. Runtimes earn the full 25 from Transformers, vLLM, SGLang, llama.cpp and Ollama. Builds earn 10, since OpenAI ships one precision, MXFP4. Terms earn 15 for Apache 2.0 with a policy that asks only for lawful use. Download earns 10, with no gate or account. Hosted earns 5, since 11 inference providers serve it on Hugging Face even though OpenAI's own API doesn't.", "b": "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." }, "scores": { "a": 75, "b": 40 } }, { "by": 30, "category": "risk", "leads": "gpt-oss-120b", "name": "Risk", "reasons": { "a": "File safety earns 25, safetensors only, with metal/model.bin a raw format and not pickle, and nothing from the repository runs on load. Provenance earns 15, files in OpenAI's linked organisation with a hash for every file. Safety evaluation earns 20, published results with SecureBio as an outside evaluator. Agent guidance earns 15 for the trained instruction hierarchy with prompt-injection results. Licence risk keeps all 15. The security programme earns 5 for OpenAI's Bugcrowd programme and disclosure policy, and the advisories half scores 0 because GitHub couldn't be checked, not because it was found missing.", "b": "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." }, "scores": { "a": 95, "b": 65 } }, { "by": 22, "category": "upkeep", "leads": "inkling-2-small", "name": "Documentation and upkeep", "reasons": { "a": "The model card earns 20, with all seven items in OpenAI's arXiv card. Training data earns 10, a general description with a cut-off. Last change earns 5, since the last change to code that runs the model was the Metal reference on 1 November 2025, a year before this check, and the files date from August 2025. It drops to 0 after 1 November 2026 unless the files, template or reference code change. Responsiveness earns 0, with no OpenAI reply in the 40 latest discussions. Version policy earns 5 as a first release. File health earns 5, the files agree but template and tokenizer reports wait without a reply.", "b": "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." }, "scores": { "a": 45, "b": 67 } }, { "by": 5, "category": "interface", "leads": "gpt-oss-120b", "name": "Agent interface", "reasons": { "a": "The chat template earns 20, a Jinja file in the repository. The tool-calling format earns 25, since OpenAI documents declarations and returned calls in harmony and tells vLLM users to parse with openai-harmony. Trained tool calling earns 10, because each call stops generation, so calls come one at a time. Structured output earns 15 for the documented Response Formats section with a JSON Schema. Reasoning control earns 10, three effort levels per request with the reasoning on the analysis channel. Context earns 10 for 131,072 trained tokens.", "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85." }, "scores": { "a": 90, "b": 85 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "OpenAI", "b": "Thinking Machines Lab", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2025-08-26", "b": "2026-11-12", "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": "3.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on documentation and upkeep.", "question": "Which is better for AI agents, gpt-oss-120b or Inkling 2 Small?" } ], "goodFor": [ { "aheadOn": [ "Reach, 75 against 40", "Risk, 95 against 65", "Agent interface, 90 against 85" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support", "slug": "gpt-oss-120b", "watchFor": "Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision" }, { "aheadOn": [ "Documentation and upkeep, 67 against 45" ], "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" } ], "history": { "gpt-oss-120b": null, "inkling-2-small": [ { "causes": [ "product" ], "date": "2026-11-12", "delta": 6.7, "from": 52.1, "fromGrade": "D", "to": 58.8, "toGrade": "C" } ] }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b.json", "title": "Agents-A1-4B vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b" }, { "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/apertus-v1-5-8b-vs-gpt-oss-120b.json", "title": "Apertus v1.5 8B vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.json", "title": "Apertus v1.5 8B vs Inkling 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"json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ripple-65b-preview.json", "title": "gpt-oss-120b vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-sensenova-loop-9b-preview.json", "title": "gpt-oss-120b vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b.json", "title": "gpt-oss-120b vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-spark-x2-6-4b.json", "title": "gpt-oss-120b vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-step-3-7-flash.json", "title": "gpt-oss-120b vs Step 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Small", "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-inkling-small.json", "title": "Inkling 2 Small vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Inkling 2 Small vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-kimi-k3.json", "title": "Inkling 2 Small vs Kimi K3", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-kimi-k3-1-pro.json", "title": "Inkling 2 Small vs Kimi K3.1 Pro", "url": 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LongCat-2.5", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Inkling 2 Small vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-flash-rl.json", "title": "Inkling 2 Small vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-o-4-5.json", "title": "Inkling 2 Small vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minicpm-v-4-7-1b.json", "title": "Inkling 2 Small vs MiniCPM-V 4.7 1B", "url": 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"title": "Inkling 2 Small vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Inkling 2 Small vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Inkling 2 Small vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b.json", "title": "Inkling 2 Small vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-nano-30b-a3b" }, { "json": 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"https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b.json", "title": "Inkling 2 Small vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Inkling 2 Small vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.json", "title": "Inkling 2 Small vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.json", "title": "Inkling 2 Small vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b" }, { "json": 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"url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.json", "title": "Inkling 2 Small vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.json", "title": "Inkling 2 Small vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.json", "title": "Inkling 2 Small vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.json", "title": "Inkling 2 Small vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next.json", "title": "Inkling 2 Small vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Inkling 2 Small vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct.json", "title": "Inkling 2 Small vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct.json", "title": "Inkling 2 Small vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct.json", "title": "Inkling 2 Small vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.json", "title": "Inkling 2 Small vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2.json", "title": "Inkling 2 Small vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint.json", "title": "Inkling 2 Small vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview.json", "title": "Inkling 2 Small vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview.json", "title": "Inkling 2 Small vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.json", "title": "Inkling 2 Small vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b.json", "title": "Inkling 2 Small vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash.json", "title": "Inkling 2 Small vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b.json", "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b.json", "title": "Inkling 2 Small vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2.json", "title": "Inkling 2 Small vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.json", "title": "Inkling 2 Small vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b.json", "title": "Inkling 2 Small vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b.json", "title": "Inkling 2 Small vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small.json", "title": "Inkling vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 35, "edge": "gpt-oss-120b", "gpt-oss-120b": 75, "inkling-2-small": 40, "key": "reach", "name": "Reach", "weight": 25 }, { "by": 30, "edge": "gpt-oss-120b", "gpt-oss-120b": 95, "inkling-2-small": 65, "key": "risk", "name": "Risk", "weight": 20 }, { "by": 5, "edge": "gpt-oss-120b", "gpt-oss-120b": 90, "inkling-2-small": 85, "key": "interface", "name": "Agent interface", "weight": 10 }, { "by": 22, "edge": "inkling-2-small", "gpt-oss-120b": 45, "inkling-2-small": 67, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on documentation and upkeep. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "gpt-oss-120b": "A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small", "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.min.md" }, "markdown": "gpt-oss-120b scores 70.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- gpt-oss-120b: grade BB, 70.2/100, rank #6 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-120b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json\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- 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### gpt-oss-120b (BB)\n\nGood for: Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support\n\nAhead on:\n- Reach, 75 against 40\n- Risk, 95 against 65\n- Agent interface, 90 against 85\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision\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- Documentation and upkeep, 67 against 45\n\nWatch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory\n\n\n## Why the edge\n\n### Reach: gpt-oss-120b +35\n\n- gpt-oss-120b (75): Memory earns 10, because the smallest 4-bit build, Ollama's 65 GB gpt-oss:120b, needs about 78 GB with the fifth added, which fits the reference machine but not 64 GB. Runtimes earn the full 25 from Transformers, vLLM, SGLang, llama.cpp and Ollama. Builds earn 10, since OpenAI ships one precision, MXFP4. Terms earn 15 for Apache 2.0 with a policy that asks only for lawful use. Download earns 10, with no gate or account. Hosted earns 5, since 11 inference providers serve it on Hugging Face even though OpenAI's own API doesn't.\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\n### Risk: gpt-oss-120b +30\n\n- gpt-oss-120b (95): File safety earns 25, safetensors only, with metal/model.bin a raw format and not pickle, and nothing from the repository runs on load. Provenance earns 15, files in OpenAI's linked organisation with a hash for every file. Safety evaluation earns 20, published results with SecureBio as an outside evaluator. Agent guidance earns 15 for the trained instruction hierarchy with prompt-injection results. Licence risk keeps all 15. The security programme earns 5 for OpenAI's Bugcrowd programme and disclosure policy, and the advisories half scores 0 because GitHub couldn't be checked, not because it was found missing.\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\n### Documentation and upkeep: Inkling 2 Small +22\n\n- gpt-oss-120b (45): The model card earns 20, with all seven items in OpenAI's arXiv card. Training data earns 10, a general description with a cut-off. Last change earns 5, since the last change to code that runs the model was the Metal reference on 1 November 2025, a year before this check, and the files date from August 2025. It drops to 0 after 1 November 2026 unless the files, template or reference code change. Responsiveness earns 0, with no OpenAI reply in the 40 latest discussions. Version policy earns 5 as a first release. File health earns 5, the files agree but template and tokenizer reports wait without a reply.\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\n### Agent interface: gpt-oss-120b +5\n\n- gpt-oss-120b (90): The chat template earns 20, a Jinja file in the repository. The tool-calling format earns 25, since OpenAI documents declarations and returned calls in harmony and tells vLLM users to parse with openai-harmony. Trained tool calling earns 10, because each call stops generation, so calls come one at a time. Structured output earns 15 for the documented Response Formats section with a JSON Schema. Reasoning control earns 10, three effort levels per request with the reasoning on the analysis channel. Context earns 10 for 131,072 trained tokens.\n- Inkling 2 Small (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n\n## Score by category\n\n| Category | Weight | gpt-oss-120b | Inkling 2 Small | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 75 | 40 | gpt-oss-120b +35 |\n| Risk | 20% (20 this run) | 95 | 65 | gpt-oss-120b +30 |\n| Agent interface | 10% (10 this run) | 90 | 85 | gpt-oss-120b +5 |\n| Documentation and upkeep | 10% (10 this run) | 45 | 67 | Inkling 2 Small +22 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **70.2 · BB** | **58.8 · C** | |\n\n## Facts side by side\n\n| Fact | gpt-oss-120b | Inkling 2 Small |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenAI | Thinking Machines Lab |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-08-26 | 2026-11-12 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 3.5/5 (4) | none |\n\n## How the scores have moved\n\n### gpt-oss-120b\n\nNo score change since it was listed.\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n## Verdicts\n\n**gpt-oss-120b.** A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports since August 2025.\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## Before you call either\n\n### gpt-oss-120b\n\n1. Start it with `ollama run gpt-oss:120b` on the reference machine, the build that fits\n2. On the Strix Halo machine raise the GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is below the 78 GB it needs\n3. With vLLM use `vllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice` per vLLM's recipe, or parse raw output with openai-harmony\n4. Always use the harmony format through the chat template or openai-harmony, the card says it won't work correctly otherwise\n5. Set `Reasoning: low` in the system message for short tasks, medium is the default\n6. Pass the reasoning back after a tool call until the final answer, and keep the analysis channel away from end users\n7. Expect one tool call per turn and loop, don't wait for parallel calls\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## Questions\n\n### Which is better for AI agents, gpt-oss-120b or Inkling 2 Small?\n\ngpt-oss-120b scores 70.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. Inkling 2 Small leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gpt-oss-120b\", \"b\": \"inkling-2-small\"}`. From a terminal: `anchor compare gpt-oss-120b inkling-2-small`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json and https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json\n\n## Other comparisons with gpt-oss-120b or Inkling 2 Small\n\n- [Agents-A1-4B vs gpt-oss-120b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-120b.md)\n- [Agents-A1-4B vs Inkling 2 Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.md)\n- [Apertus v1.5 8B vs gpt-oss-120b](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-120b.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- [Apodex-1.1-mini vs gpt-oss-120b](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-120b.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- [Arete-27B vs gpt-oss-120b](https://www.anchorterminal.com/compare/arete-27b-vs-gpt-oss-120b.md)\n- [Arete-27B vs Inkling 2 Small](https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small.md)\n- [BigBang-v1 vs gpt-oss-120b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-120b.md)\n- [BigBang-v1 vs Inkling 2 Small](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.md)\n- [Carbon-X vs gpt-oss-120b](https://www.anchorterminal.com/compare/carbon-x-vs-gpt-oss-120b.md)\n- [Carbon-X vs Inkling 2 Small](https://www.anchorterminal.com/compare/carbon-x-vs-inkling-2-small.md)\n- [Cola2 vs gpt-oss-120b](https://www.anchorterminal.com/compare/cola2-vs-gpt-oss-120b.md)\n- [Cola2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/cola2-vs-inkling-2-small.md)\n- [Cosmos-Reason2-2B vs gpt-oss-120b](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b.md)\n- [Cosmos-Reason2-2B vs Inkling 2 Small](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-2-small.md)\n- [Darwin-36B-Opus vs gpt-oss-120b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-120b.md)\n- [Darwin-36B-Opus vs Inkling 2 Small](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-2-small.md)\n- [DeepSeek-V3.2 vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-120b.md)\n- [DeepSeek-V3.2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-2-small.md)\n- [DeepSeek V4.1 Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-gpt-oss-120b.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-Flash-0731 vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-gpt-oss-120b.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- [Devstral Small 2 vs gpt-oss-120b](https://www.anchorterminal.com/compare/devstral-small-2-vs-gpt-oss-120b.md)\n- [Devstral Small 2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling-2-small.md)\n- [DiffusionGemma 26B A4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-gpt-oss-120b.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- [EXAONE 4.5 33B vs gpt-oss-120b](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-120b.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- [Gemma 4 12B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-gpt-oss-120b.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 26B A4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-gpt-oss-120b.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 31B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-gpt-oss-120b.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 E2B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-gpt-oss-120b.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 E4B IT vs gpt-oss-120b](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-gpt-oss-120b.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- [GLM-4.5-Air vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-4-5-air-vs-gpt-oss-120b.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-4.7-Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-gpt-oss-120b.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-5.3-Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-120b.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 vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.md)\n- [GLM-5.3 vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-2-small.md)\n- [gpt-oss-120b vs gpt-oss-20b](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-gpt-oss-20b.md)\n- [gpt-oss-120b vs Granite 4.2 30B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-granite-4-2-30b.md)\n- [gpt-oss-120b vs Granite 4.2 3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-granite-4-2-3b.md)\n- [gpt-oss-120b vs Granite 4.2 8B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-granite-4-2-8b.md)\n- [gpt-oss-120b vs Hy-Memory-30B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy-memory-30b-a3b.md)\n- [gpt-oss-120b vs Hy3](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.md)\n- [gpt-oss-120b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling.md)\n- [gpt-oss-120b vs Inkling-Small](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small.md)\n- [gpt-oss-120b vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [gpt-oss-120b vs Kimi K3](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3.md)\n- [gpt-oss-120b vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3-1-pro.md)\n- [gpt-oss-120b vs Kolibri-1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kolibri-1.md)\n- [gpt-oss-120b vs Kronos](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kronos.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-120b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.md)\n- [gpt-oss-120b vs Laguna XS 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-xs-2-1.md)\n- [gpt-oss-120b vs LBS-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lbs-27b.md)\n- [gpt-oss-120b vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm2-5-2-6b.md)\n- [gpt-oss-120b vs LFM3-1.7B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b.md)\n- [gpt-oss-120b vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-audio-2b.md)\n- [gpt-oss-120b vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-omni-2b.md)\n- [gpt-oss-120b vs LFM3-VL-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-vl-2b.md)\n- [gpt-oss-120b vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-0-tiny.md)\n- [gpt-oss-120b vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-1-flash-1019.md)\n- [gpt-oss-120b vs LongCat-2.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-longcat-2-5.md)\n- [gpt-oss-120b vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [gpt-oss-120b vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mimo-v2-6-flash-rl.md)\n- [gpt-oss-120b vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-o-4-5.md)\n- [gpt-oss-120b vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-v-4-7-1b.md)\n- [gpt-oss-120b vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-v-4-7-35b-a3b.md)\n- [gpt-oss-120b vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm5-2b.md)\n- [gpt-oss-120b vs MiniMax-M2.5](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5.md)\n- [gpt-oss-120b vs MiniMax-M2.7](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-7.md)\n- [gpt-oss-120b vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m3-1-flash.md)\n- [gpt-oss-120b vs Mistral Large 4](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-mistral-large-4.md)\n- [gpt-oss-120b vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-muse-glimmer-30b.md)\n- [gpt-oss-120b vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nanbeige-4-2-3b.md)\n- [gpt-oss-120b vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nanbeige-4-3-33b.md)\n- [gpt-oss-120b vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [gpt-oss-120b vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-30b-a3b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-4b.md)\n- [gpt-oss-120b vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [gpt-oss-120b vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-super-120b-a12b.md)\n- [gpt-oss-120b vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-ultra-550b-a55b.md)\n- [gpt-oss-120b vs North Mini Code 1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-north-mini-code-1-0.md)\n- [gpt-oss-120b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.md)\n- [gpt-oss-120b vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-olmo-3-7b-think.md)\n- [gpt-oss-120b vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-122b.md)\n- [gpt-oss-120b vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-35b-a3b.md)\n- [gpt-oss-120b vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-397b.md)\n- [gpt-oss-120b vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-9b.md)\n- [gpt-oss-120b vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-otel-2-0-llm-31b-it.md)\n- [gpt-oss-120b vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen-agentworld-35b-a3b.md)\n- [gpt-oss-120b vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [gpt-oss-120b vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-4b-instruct-2507.md)\n- [gpt-oss-120b vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-0-8b.md)\n- [gpt-oss-120b vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-122b-a10b.md)\n- [gpt-oss-120b vs Qwen3.5-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-2b.md)\n- [gpt-oss-120b vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-397b-a17b.md)\n- [gpt-oss-120b vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-4b.md)\n- [gpt-oss-120b vs Qwen3.5-9B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-5-9b.md)\n- [gpt-oss-120b vs Qwen3.6-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-6-27b.md)\n- [gpt-oss-120b vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-6-35b-a3b.md)\n- [gpt-oss-120b vs Qwen3.8-27B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-27b.md)\n- [gpt-oss-120b vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-8-flash-next.md)\n- [gpt-oss-120b vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-coder-next.md)\n- [gpt-oss-120b vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-2b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-32b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-4b-instruct.md)\n- [gpt-oss-120b vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwen3-vl-8b-instruct.md)\n- [gpt-oss-120b vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-qwopus3-8-27b-flash-v2.md)\n- [gpt-oss-120b vs Recursive Flint](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-recursive-flint.md)\n- 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Small vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.md)\n- [Inkling 2 Small vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b.md)\n- [Inkling 2 Small vs ZAYA1-8B](https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b.md)\n- [Inkling vs Inkling 2 Small](https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.8", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": 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