{ "data": { "a": { "slug": "gpt-oss-20b", "name": "gpt-oss-20b", "vendor": "OpenAI", "vendorUrl": "https://openai.com", "kind": "weights", "category": "open-weights", "summary": "gpt-oss-20b is OpenAI's open-weight mixture-of-experts reasoning model, 21B parameters with 3.6B active and a 131,072-token context, published on Hugging Face in MXFP4 under Apache 2.0 and trained on the harmony prompt format.", "url": "https://www.anchorterminal.com/tools/gpt-oss-20b", "markdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json", "repo": "https://huggingface.co/openai/gpt-oss-20b", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "openai/gpt-oss-20b" }, { "registry": "ollama", "name": "gpt-oss:20b" }, { "registry": "pypi", "name": "gpt-oss" }, { "registry": "pypi", "name": "openai-harmony" } ], "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 that asks users to comply with applicable law. Running it yourself costs the hardware, about 13.8 GB of weights, and OpenAI says it runs within 16 GB of memory (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-20b", "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": 69.9, "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": 6, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 49, "interface": 90, "reach": 90, "risk": 85, "upkeep": 42 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.", "bestFor": "Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time", "strengths": [ "Model code in released Transformers, vLLM, SGLang and llama.cpp, plus a 14 GB build in Ollama's library", "Fits a 24 GB machine at OpenAI's own MXFP4 precision, the one every evaluation used", "Apache 2.0 with no gate, no account and a usage policy that only asks users to follow the law", "Harmony guide documents tool declarations, call parsing, JSON Schema output and three reasoning levels, with OpenAI's own parser", "Trained on an instruction hierarchy against prompt injection, with OpenAI's results for it published" ], "weaknesses": [ "No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered", "One tool call per message", "Reasoning can be lowered but not switched off", "Only one quantised build from OpenAI, and its weights and template haven't changed since August 2025", "Safety results for this size are OpenAI's own, and it trails o4-mini on the instruction hierarchy" ], "agentNotes": [ "Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel", "Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it", "Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel", "Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default", "Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message", "Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users", "Expect one tool call per turn; run several in sequence rather than in parallel" ], "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": 69.9 } ], "editorialScores": { "capability": 49, "interface": 90, "reach": 90, "risk": 85, "upkeep": 42 }, "provenanceScore": 87, "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": "ollama run gpt-oss:20b\n# or with vLLM:\nvllm serve openai/gpt-oss-20b", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"gpt-oss:20b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/gpt-oss-20b" }, "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-codex", "gpt-oss-120b" ], "weights": { "trainedBy": "OpenAI", "params": "20.91B", "active": "3.61B", "context": 131072, "goodFor": "Text reasoning model for agents and coding, with function calling, built-in browser and Python tools and low, medium or high reasoning, in the harmony format.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "gpt-oss-20b", "url": "https://huggingface.co/openai/gpt-oss-20b", "who": "publisher", "precision": "mxfp4", "sizeGB": 13.8, "memoryGB": 24, "format": "safetensors", "note": "MoE weights in MXFP4, the rest BF16, the precision OpenAI evaluated. original/ and metal/ hold the same weights for OpenAI's reference code. vLLM's gpt-oss recipe lists MI300x, MI325x, MI355x and Radeon AI PRO R9700 on AMD, not gfx1151" }, { "name": "ollama gpt-oss:20b", "url": "https://ollama.com/library/gpt-oss:20b", "who": "ollama", "precision": "mxfp4", "sizeGB": 14, "memoryGB": 24, "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" } ], "run": "ollama run gpt-oss:20b", "runBuild": "ollama gpt-oss:20b", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "OpenAI", "family": "gpt-oss", "url": "https://www.anchorterminal.com/open-weights/#openai", "others": [ { "name": "gpt-oss-120b", "url": "https://huggingface.co/openai/gpt-oss-120b", "params": "117B total, 5.1B active (MoE)", "listing": "https://www.anchorterminal.com/tools/gpt-oss-120b" }, { "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 in USAGE_POLICY and the model card; the LICENSE file's copyright line is the unfilled Apache template)", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, years before the company was founded in 2015, so domain age flatters it.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/openai/gpt-oss-20b/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "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 repository's commit history, whose messages say what changed for some commits (the chat template on 7 and 8 August 2025, `\u003c|call|\u003e` as an end token on 13 August 2025) and not for others (README updates).", "openai.com/.well-known/security.txt answered 200, signed, with a Bugcrowd contact and a coordinated disclosure policy, but no Expires field, which RFC 9116 requires. Recorded as valid, as on the openai-api listing, since the data has no value for a file without one.", "openai.com/index/introducing-gpt-oss/ and openai.com/open-models/ answered 403 to our reader on 21 October 2026, so OpenAI's announcement wasn't read." ], "score": 87 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt-oss-20b.json" }, "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against Nemotron 3 Nano 30B A3B's 67.1 (B), and leads in 2 of 5 scored categories. Nemotron 3 Nano 30B A3B leads on documentation and upkeep.", "b": { "slug": "nemotron-3-nano-30b-a3b", "name": "Nemotron 3 Nano 30B A3B", "vendor": "NVIDIA", "vendorUrl": "https://developer.nvidia.com/nemotron", "kind": "weights", "category": "open-weights", "summary": "Nemotron 3 Nano 30B A3B is NVIDIA's open-weight hybrid Mamba-Transformer mixture of experts for reasoning and agent work, 30B parameters with 3.5B active, published on Hugging Face in BF16, FP8 and NVFP4.", "url": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b", "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-30b-a3b.json", "repo": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16", "license": "NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence)", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4" }, { "registry": "ollama", "name": "nemotron-3-nano:30b" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The BF16, FP8 and NVFP4 repositories are not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the NVIDIA Nemotron Open Model License. Running it yourself costs the hardware, 63.2 GB for the BF16 files, 32.7 GB for FP8, 19.4 GB for NVFP4 and 18 GB for Ollama's default 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/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "mamba", "reasoning", "tool-calling", "commercial-licence", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-08-24", "graded": true, "anchor": { "graded": true, "score": 67.1, "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": 10, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 46, "interface": 90, "reach": 90, "risk": 60, "upkeep": 75 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A fast hybrid Mamba-Transformer cousin with 3.5B active parameters for reasoning and tool calling over very long inputs, in every major local runtime. A 4-bit build needs about 22 to 23 GB. The main risks are that NVIDIA's documented vLLM path runs repository code, no safety results are published and NVIDIA hasn't answered reports since March.", "bestFor": "Agents with a 24 to 32 GB GPU or Mac that want a quick tool-calling and reasoning cousin with very long context.", "strengths": [ "Runs in released llama.cpp, Ollama, vLLM, SGLang, LM Studio and Transformers", "NVIDIA's own FP8 and NVFP4 builds beside BF16, and ungated files in NVIDIA's own organisation with a SHA-256 for every shard", "Tool calling documented end to end with a named parser, several calls to a turn, and thinking that can be turned off or budgeted", "1M tokens of input with no position-encoding scaling", "Full model card and a detailed data card with cut-offs, with much of the training data released" ], "weaknesses": [ "The documented vLLM, SGLang and TensorRT-LLM commands pass trust-remote-code and load a parser file from the repository", "No safety or bias results published, though the subcards say both were run", "No NVIDIA reply on any of the 10 discussions opened since 1 March 2026, including a chat-template report", "Licence replaced eight days after release with no dated note, and the subcards still link the old one", "Structured output isn't documented, and the custom licence isn't OSI-approved" ], "agentNotes": [ "Start it with `ollama run nemotron-3-nano:30b` (18 GB MLX on a Mac, 24 GB q4_K_M elsewhere)", "On the reference machine use BF16 with vLLM, after `wget https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/resolve/main/nano_v3_reasoning_parser.py`, then `vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 --max-model-len 262144 --trust-remote-code --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser-plugin nano_v3_reasoning_parser.py --reasoning-parser nano_v3`", "NVFP4 needs an NVIDIA Blackwell GPU, and FP8 isn't documented on gfx1151", "Without the qwen3_coder tool parser and the nano_v3 reasoning parser, tool calls and reasoning come back as plain text", "Card sampling is temperature 0.6 and top_p 0.95 for tool calling, temperature 1.0 and top_p 1.0 for reasoning", "Thinking is on by default, so pass enable_thinking as false in chat_template_kwargs for short tasks", "Set VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 and raise --max-model-len only when you need more than 262,144 tokens", "In SGLang the main branch names the reasoning parser nemotron_3, not the card's nano_v3", "Filter untrusted tool results before they reach the model, as NVIDIA warns prompt injection can lead to code execution", "Validate JSON output yourself or use the runtime's guided decoding, since none is documented for the model" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.1 } ], "editorialScores": { "capability": 46, "interface": 90, "reach": 90, "risk": 60, "upkeep": 75 }, "provenanceScore": 73, "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": "ollama run nemotron-3-nano:30b\n# or, with vLLM per NVIDIA's card (the reasoning parser is a file from the repository):\nwget https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/resolve/main/nano_v3_reasoning_parser.py\nvllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 --max-model-len 262144 --trust-remote-code \\\n --enable-auto-tool-choice --tool-call-parser qwen3_coder \\\n --reasoning-parser-plugin nano_v3_reasoning_parser.py --reasoning-parser nano_v3", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"nemotron-3-nano:30b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/nemotron-3-nano-30b-a3b" }, "sameCompany": [ "nemotron-3-5-super-vl", "nvidia-nemo-retriever", "nemo-guardrails", "nemotron-3-5-asr-streaming-0-6b", "parakeet-tdt-0-6b-v3", "cosmos-reason2-2b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-super-120b-a12b", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "builtOn": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16", "params": "30B", "active": "3.5B", "context": 1048576, "goodFor": "Hybrid Mamba-Transformer mixture of experts for reasoning and agent work, text only, with tool calling and a reasoning budget.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 19.3, "memoryGB": 24, "format": "safetensors", "note": "NVFP4 needs NVIDIA Blackwell" }, { "name": "ollama nemotron-3-nano:30b", "url": "https://ollama.com/library/nemotron-3-nano:30b", "who": "ollama", "precision": "q4_k_m", "sizeGB": 24, "memoryGB": 32, "format": "ollama", "runsOn": [ "Ollama" ], "note": "digest 7487f38ecf24. Size as Ollama's tags page shows it, rounded to whole GB above 10 GB; the Linux build is the llama.cpp variant" }, { "name": "NVIDIA-Nemotron-3-Nano-30B-A3B-FP8", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 32.7, "memoryGB": 48, "format": "safetensors" }, { "name": "NVIDIA-Nemotron-3-Nano-30B-A3B-BF16", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16", "who": "publisher", "precision": "bf16", "sizeGB": 63.2, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4 --max-model-len 262144 --trust-remote-code --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser-plugin nano_v3_reasoning_parser.py --reasoning-parser nano_v3", "runBuild": "NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "NVIDIA (Nemotron)", "family": "Nemotron 3", "url": "https://www.anchorterminal.com/open-weights/#nvidia", "others": [ { "name": "Nemotron 3 Nano 30B-A3B Base", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16", "params": "30B total, 3B active" }, { "name": "Nemotron 3 Super 120B-A12B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", "params": "120B total, 12B active", "listing": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b" }, { "name": "Nemotron 3 Super 120B-A12B Base", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16", "params": "120B total, 12B active" }, { "name": "Nemotron 3 Nano 4B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16", "params": "4B", "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-4b" }, { "name": "Nemotron 3 Nano Omni 30B-A3B Reasoning", "url": "https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16", "params": "30B total, 3B active", "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning" }, { "name": "Nemotron 3 Ultra 550B-A55B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16", "params": "550B total, 55B active", "listing": "https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b" }, { "name": "Nemotron 3 Ultra 550B-A55B Base", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-Base-BF16", "params": "550B total, 55B active" }, { "name": "Nemotron 3 Ultra 550B-A55B GenRM", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-GenRM", "params": "550B total, 55B active" }, { "name": "Nemotron 3.5 Lightning 30B-A3B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16", "params": "30B total, 3B active", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-lightning-30b-a3b" }, { "name": "Nemotron 3.5 Lightning 30B-A3B Base", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-Base-BF16", "params": "30B total, 3B active" }, { "name": "Nemotron 3.5 Super VL 120B-A12B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16", "params": "120B total, 12B active", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-super-vl" }, { "name": "Nemotron 3.5 Super VL 120B-A12B Base", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-Base-BF16", "params": "120B total, 12B active" }, { "name": "Nemotron 3.5 Bolt 74B-A9B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16", "params": "74B total, 9B active" }, { "name": "Nemotron Labs 3 Elastic 30B-A3B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Elastic-30B-A3B-BF16", "params": "30B total, 3B active" }, { "name": "Nemotron Labs 3 Puzzle 75B-A9B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Puzzle-75B-A9B-BF16", "params": "75B total, 9B active" }, { "name": "Nemotron 3 Labs Ultra Math SFT", "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-SFT", "params": "550B total, 55B active" }, { "name": "Nemotron 3 Labs Ultra Math RL", "url": "https://huggingface.co/nvidia/Nemotron-3-Labs-Ultra-Math-RL", "params": "550B total, 55B active" }, { "name": "Nemotron Labs 3 Competitive Coding 550B-A55B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-Labs-3-Competitive-Coding-550B-A55B-NVFP4", "params": "550B total, 55B active" }, { "name": "nemotron-3.5-asr-streaming-0.6b", "url": "https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b", "params": "0.6B (638M per the safetensors count)", "listing": "https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b" } ], "olderCount": 43, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "NVIDIA Corporation", "domain": "nvidia.com", "domainRegistered": "1993-04-20", "endpointOnVendorDomain": null, "terms": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The card names NVIDIA Corporation as model developer, and the licence names NVIDIA. RDAP gives nvidia.com a registration date of 20 April 1993.", "Nothing is hosted for this listing, so the Nemotron Open Model License stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history. A few messages say what changed (a reasoning budget example on 19 December 2025, a 1M-context vLLM example on 8 January 2026); most read Update README.md.", "www.nvidia.com/.well-known/security.txt answered 403 on 21 October 2026. Vulnerability reports go to NVIDIA PSIRT, linked from the card, which publishes a disclosure policy and security bulletins." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "OpenAI", "b": "NVIDIA", "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": "NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2025-08-26", "b": "2026-08-24", "name": "Last release" }, { "a": "no document linked", "b": "", "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": "3.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "gpt-oss-20b scores 69.9 (B) on agent readiness against Nemotron 3 Nano 30B A3B's 67.1 (B), and leads in 2 of 5 scored categories. 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"url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-super-120b-a12b.json", "title": "Nemotron 3 Nano 30B A3B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-ultra-550b-a55b.json", "title": "Nemotron 3 Nano 30B A3B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0.json", "title": "Nemotron 3 Nano 30B A3B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0" }, { "json": 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"https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-4b-instruct-2507.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-0-8b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-122b-a10b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-2b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-397b-a17b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-4b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-9b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-6-27b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-6-35b-a3b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-27b.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-flash-next.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-coder-next.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-2b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-32b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-4b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-8b-instruct.json", "title": "Nemotron 3 Nano 30B A3B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwopus3-8-27b-flash-v2.json", "title": "Nemotron 3 Nano 30B A3B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-smollm3-3b.json", "title": "Nemotron 3 Nano 30B A3B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-spark-x2-6-4b.json", "title": "Nemotron 3 Nano 30B A3B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-swift-1-5-qwen3-8-27b.json", "title": "Nemotron 3 Nano 30B A3B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Nemotron 3 Nano 30B A3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-thinkingcap-qwen3-8-27b.json", "title": "Nemotron 3 Nano 30B A3B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "by": 3, "edge": "gpt-oss-20b", "gpt-oss-20b": 49, "key": "capability", "name": "Capability", "nemotron-3-nano-30b-a3b": 46, "weight": 35 }, { "by": 0, "edge": "", "gpt-oss-20b": 90, "key": "reach", "name": "Reach", "nemotron-3-nano-30b-a3b": 90, "weight": 25 }, { "by": 25, "edge": "gpt-oss-20b", "gpt-oss-20b": 85, "key": "risk", "name": "Risk", "nemotron-3-nano-30b-a3b": 60, "weight": 20 }, { "by": 0, "edge": "", "gpt-oss-20b": 90, "key": "interface", "name": "Agent interface", "nemotron-3-nano-30b-a3b": 90, "weight": 10 }, { "by": 33, "edge": "nemotron-3-nano-30b-a3b", "gpt-oss-20b": 42, "key": "upkeep", "name": "Documentation and upkeep", "nemotron-3-nano-30b-a3b": 75, "weight": 10 } ], "summary": "gpt-oss-20b scores 69.9 (B) on agent readiness against Nemotron 3 Nano 30B A3B's 67.1 (B), and leads in 2 of 5 scored categories. Nemotron 3 Nano 30B A3B leads on documentation and upkeep. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "gpt-oss-20b": "gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.", "nemotron-3-nano-30b-a3b": "A fast hybrid Mamba-Transformer cousin with 3.5B active parameters for reasoning and tool calling over very long inputs, in every major local runtime. A 4-bit build needs about 22 to 23 GB. The main risks are that NVIDIA's documented vLLM path runs repository code, no safety results are published and NVIDIA hasn't answered reports since March." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b", "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b.min.md" }, "markdown": "gpt-oss-20b scores 69.9 (B) on agent readiness against Nemotron 3 Nano 30B A3B's 67.1 (B), and leads in 2 of 5 scored categories. Nemotron 3 Nano 30B A3B leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- gpt-oss-20b: grade B, 69.9/100, rank #8 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-20b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json\n- Nemotron 3 Nano 30B A3B: grade B, 67.1/100, rank #12 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-30b-a3b.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### gpt-oss-20b (B)\n\nGood for: Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time\n\nAhead on:\n- Risk, 85 against 60\n\nWatch for: No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered\n\n### Nemotron 3 Nano 30B A3B (B)\n\nGood for: Agents with a 24 to 32 GB GPU or Mac that want a quick tool-calling and reasoning cousin with very long context.\n\nAhead on:\n- Documentation and upkeep, 75 against 42\n\nWatch for: The documented vLLM, SGLang and TensorRT-LLM commands pass trust-remote-code and load a parser file from the repository\n\n\n## Score by category\n\n| Category | Weight | gpt-oss-20b | Nemotron 3 Nano 30B A3B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 49 | 46 | gpt-oss-20b +3 |\n| Reach | 25% (25 this run) | 90 | 90 | even |\n| Risk | 20% (20 this run) | 85 | 60 | gpt-oss-20b +25 |\n| Agent interface | 10% (10 this run) | 90 | 90 | even |\n| Documentation and upkeep | 10% (10 this run) | 42 | 75 | Nemotron 3 Nano 30B A3B +33 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.9 · B** | **67.1 · B** | |\n\n## Facts side by side\n\n| Fact | gpt-oss-20b | Nemotron 3 Nano 30B A3B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | OpenAI | NVIDIA |\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 | NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-08-26 | 2026-08-24 |\n| Terms last updated | 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) | 3.3/5 (4) |\n\n## Verdicts\n\n**gpt-oss-20b.** gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.\n\n**Nemotron 3 Nano 30B A3B.** A fast hybrid Mamba-Transformer cousin with 3.5B active parameters for reasoning and tool calling over very long inputs, in every major local runtime. A 4-bit build needs about 22 to 23 GB. The main risks are that NVIDIA's documented vLLM path runs repository code, no safety results are published and NVIDIA hasn't answered reports since March.\n\n## Before you call either\n\n### gpt-oss-20b\n\n1. Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel\n2. Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it\n3. Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `\u003c|call|\u003e`, reasoning on the analysis channel\n4. Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default\n5. Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message\n6. Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users\n7. Expect one tool call per turn; run several in sequence rather than in parallel\n\n### Nemotron 3 Nano 30B A3B\n\n1. Start it with `ollama run nemotron-3-nano:30b` (18 GB MLX on a Mac, 24 GB q4_K_M elsewhere)\n2. On the reference machine use BF16 with vLLM, after `wget https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/resolve/main/nano_v3_reasoning_parser.py`, then `vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 --max-model-len 262144 --trust-remote-code --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser-plugin nano_v3_reasoning_parser.py --reasoning-parser nano_v3`\n3. NVFP4 needs an NVIDIA Blackwell GPU, and FP8 isn't documented on gfx1151\n4. Without the qwen3_coder tool parser and the nano_v3 reasoning parser, tool calls and reasoning come back as plain text\n5. Card sampling is temperature 0.6 and top_p 0.95 for tool calling, temperature 1.0 and top_p 1.0 for reasoning\n6. Thinking is on by default, so pass enable_thinking as false in chat_template_kwargs for short tasks\n7. Set VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 and raise --max-model-len only when you need more than 262,144 tokens\n8. In SGLang the main branch names the reasoning parser nemotron_3, not the card's nano_v3\n9. Filter untrusted tool results before they reach the model, as NVIDIA warns prompt injection can lead to code execution\n10. Validate JSON output yourself or use the runtime's guided decoding, since none is documented for the model\n\n## Questions\n\n### Which is better for AI agents, gpt-oss-20b or Nemotron 3 Nano 30B A3B?\n\ngpt-oss-20b scores 69.9 (B) on agent readiness against Nemotron 3 Nano 30B A3B's 67.1 (B), and leads in 2 of 5 scored categories. Nemotron 3 Nano 30B A3B leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-30b-a3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gpt-oss-20b\", \"b\": \"nemotron-3-nano-30b-a3b\"}`. From a terminal: `anchor compare gpt-oss-20b nemotron-3-nano-30b-a3b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-30b-a3b.json\n\n## Other comparisons with gpt-oss-20b or Nemotron 3 Nano 30B A3B\n\n- [Agents-A1-4B vs gpt-oss-20b](https://www.anchorterminal.com/compare/agents-a1-4b-vs-gpt-oss-20b.md)\n- [Agents-A1-4B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-nano-30b-a3b.md)\n- [Apertus v1.5 8B vs gpt-oss-20b](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-gpt-oss-20b.md)\n- [Apertus v1.5 8B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-nano-30b-a3b.md)\n- [Apodex-1.1-mini vs gpt-oss-20b](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-gpt-oss-20b.md)\n- [Apodex-1.1-mini vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-nemotron-3-nano-30b-a3b.md)\n- [BigBang-v1 vs gpt-oss-20b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-20b.md)\n- [BigBang-v1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-nano-30b-a3b.md)\n- [Cosmos-Reason2-2B vs gpt-oss-20b](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.md)\n- [Cosmos-Reason2-2B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-30b-a3b.md)\n- [Darwin-36B-Opus vs gpt-oss-20b](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-gpt-oss-20b.md)\n- [Darwin-36B-Opus vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-nano-30b-a3b.md)\n- [DeepSeek-V3.2 vs gpt-oss-20b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-30b-a3b.md)\n- [DeepSeek V4.1 Flash vs gpt-oss-20b](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-gpt-oss-20b.md)\n- [DeepSeek V4.1 Flash vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-nemotron-3-nano-30b-a3b.md)\n- [DeepSeek-V4-Flash-0731 vs gpt-oss-20b](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-gpt-oss-20b.md)\n- [DeepSeek-V4-Flash-0731 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-nemotron-3-nano-30b-a3b.md)\n- [DiffusionGemma 26B A4B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-gpt-oss-20b.md)\n- [DiffusionGemma 26B A4B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [Gemma 4 12B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-gpt-oss-20b.md)\n- [Gemma 4 12B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [Gemma 4 26B A4B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-gpt-oss-20b.md)\n- [Gemma 4 26B A4B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [Gemma 4 31B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-gpt-oss-20b.md)\n- [Gemma 4 31B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [Gemma 4 E2B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-gpt-oss-20b.md)\n- [Gemma 4 E2B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [Gemma 4 E4B IT vs gpt-oss-20b](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-gpt-oss-20b.md)\n- [Gemma 4 E4B IT vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-4.5-Air vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-4-5-air-vs-gpt-oss-20b.md)\n- [GLM-4.5-Air vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-4.7-Flash vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-gpt-oss-20b.md)\n- [GLM-4.7-Flash vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-5.3-Flash vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-20b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-5.3 vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b.md)\n- [GLM-5.3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b.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 Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-nano-30b-a3b.md)\n- [gpt-oss-20b vs Granite 4.2 3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-granite-4-2-3b.md)\n- [gpt-oss-20b vs Hy3](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.md)\n- [gpt-oss-20b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling.md)\n- [gpt-oss-20b vs Inkling-Small](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-small.md)\n- [gpt-oss-20b vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [gpt-oss-20b vs Kimi K3](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kimi-k3.md)\n- [gpt-oss-20b vs Kolibri-1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kolibri-1.md)\n- [gpt-oss-20b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-m-1.md)\n- [gpt-oss-20b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1.md)\n- [gpt-oss-20b vs Laguna XS 2.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-xs-2-1.md)\n- [gpt-oss-20b vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm2-5-2-6b.md)\n- [gpt-oss-20b vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ling-3-0-tiny.md)\n- [gpt-oss-20b vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [gpt-oss-20b vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-o-4-5.md)\n- [gpt-oss-20b vs MiniCPM5-2B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm5-2b.md)\n- [gpt-oss-20b vs MiniMax-M2.5](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-5.md)\n- [gpt-oss-20b vs MiniMax-M2.7](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-7.md)\n- [gpt-oss-20b vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-muse-glimmer-30b.md)\n- [gpt-oss-20b vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [gpt-oss-20b vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-4b.md)\n- [gpt-oss-20b vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [gpt-oss-20b vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-super-120b-a12b.md)\n- [gpt-oss-20b vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-ultra-550b-a55b.md)\n- [gpt-oss-20b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0.md)\n- [gpt-oss-20b vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-olmo-3-7b-think.md)\n- [gpt-oss-20b vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-35b-a3b.md)\n- [gpt-oss-20b vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-397b.md)\n- [gpt-oss-20b vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-9b.md)\n- [gpt-oss-20b vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [gpt-oss-20b vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-4b-instruct-2507.md)\n- [gpt-oss-20b vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-0-8b.md)\n- [gpt-oss-20b vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-122b-a10b.md)\n- [gpt-oss-20b vs Qwen3.5-2B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-2b.md)\n- [gpt-oss-20b vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-397b-a17b.md)\n- [gpt-oss-20b vs Qwen3.5-4B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-4b.md)\n- [gpt-oss-20b vs Qwen3.5-9B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-5-9b.md)\n- [gpt-oss-20b vs Qwen3.6-27B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-6-27b.md)\n- [gpt-oss-20b vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-6-35b-a3b.md)\n- [gpt-oss-20b vs Qwen3.8-27B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-8-27b.md)\n- [gpt-oss-20b vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-8-flash-next.md)\n- [gpt-oss-20b vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [gpt-oss-20b vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-coder-next.md)\n- [gpt-oss-20b vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [gpt-oss-20b vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-2b-instruct.md)\n- [gpt-oss-20b vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [gpt-oss-20b vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-32b-instruct.md)\n- [gpt-oss-20b vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-4b-instruct.md)\n- [gpt-oss-20b vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwen3-vl-8b-instruct.md)\n- [gpt-oss-20b vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-qwopus3-8-27b-flash-v2.md)\n- [gpt-oss-20b vs SmolLM3-3B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-smollm3-3b.md)\n- [gpt-oss-20b vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-spark-x2-6-4b.md)\n- [gpt-oss-20b vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-27b.md)\n- [gpt-oss-20b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-20b vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-thinkingcap-qwen3-8-27b.md)\n- [Granite 4.2 3B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-nano-30b-a3b.md)\n- [Hy3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-30b-a3b.md)\n- [Inkling-Small vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b.md)\n- [Inkling vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-nano-30b-a3b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-nemotron-3-nano-30b-a3b.md)\n- [Kimi K3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b.md)\n- [Kolibri-1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna M.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-30b-a3b.md)\n- [LFM2.5-2.6B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-nemotron-3-nano-30b-a3b.md)\n- [Ling-3.0-tiny vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-nano-30b-a3b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-nano-30b-a3b.md)\n- [MiniCPM5-2B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-nemotron-3-nano-30b-a3b.md)\n- [MiniMax-M2.5 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-30b-a3b.md)\n- [MiniMax-M2.7 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-nemotron-3-nano-30b-a3b.md)\n- [Muse Glimmer 30B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-nemotron-3-nano-30b-a3b.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-nemotron-3-nano-30b-a3b.md)\n- [Nemotron 3 Nano 30B A3B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-nano-4b.md)\n- [Nemotron 3 Nano 30B A3B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Nemotron 3 Nano 30B A3B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-nemotron-3-super-120b-a12b.md)\n- [Nemotron 3 Nano 30B A3B vs Nemotron 3 Ultra 550B 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"https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "gpt-oss-20b vs Nemotron 3 Nano 30B A3B", "url": "" } ], "description": "gpt-oss-20b scores 69.9 (B) to Nemotron 3 Nano 30B A3B's 67.1 (B) for open-weight models you run yourself. 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