{ "data": { "a": { "slug": "inkling-small", "name": "Inkling-Small", "vendor": "Thinking Machines Lab", "vendorUrl": "https://thinkingmachines.ai", "kind": "weights", "category": "open-weights", "summary": "Inkling-Small is Thinking Machines Lab's open-weight mixture-of-experts model, 276B total and 12B active parameters, taking text, images and audio and returning text, with adjustable thinking effort, published in BF16 and NVFP4 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/inkling-small", "markdownUrl": "https://www.anchorterminal.com/tools/inkling-small.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-small.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-small.json", "repo": "https://huggingface.co/thinkingmachines/Inkling-Small", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "thinkingmachines/Inkling-Small" }, { "registry": "huggingface", "name": "thinkingmachines/Inkling-Small-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 531.9 GB for the BF16 files and 170.8 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens and $1.20 per million output tokens (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://thinkingmachines.ai/model-card/inkling-small/", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "audio", "reasoning", "tool-calling", "apache-2.0", "safetensors", "nvfp4", "self-hosted" ], "lastRelease": "2026-07-31", "graded": true, "anchor": { "graded": true, "score": 66.5, "grade": "B", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 11, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 63, "interface": 85, "reach": 55, "risk": 70, "upkeep": 82 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.", "bestFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.", "strengths": [ "Thinking Machines answered 8 of the 9 questions in its discussions", "Safetensors only, with a checksum on every LFS file in the publisher's own organisation", "Thinking effort set per request from none to the maximum, several tool calls a turn and a 1M-token context", "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers", "A training-content summary with sources, mix and a July 2026 collection cut-off", "Thinking Machines' own Tinker hosts it as beta serverless inference" ], "weaknesses": [ "The smallest build Thinking Machines publishes needs about 205 GB", "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time", "No release of ggml-org's llama.cpp, Ollama or LM Studio runs it", "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance", "Structured output isn't documented, and the card gives no dated knowledge cut-off" ], "agentNotes": [ "Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4", "Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself", "Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh", "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens", "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error", "Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card", "Use guided decoding or validate JSON yourself, since structured output isn't documented", "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.5 } ], "editorialScores": { "capability": 63, "interface": 85, "reach": 55, "risk": 70, "upkeep": 82 }, "provenanceScore": 67, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# per SGLang's cookbook, NVFP4 on 8 Blackwell GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 \\\n --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling", "http": "curl http://localhost:30000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"thinkingmachines/Inkling-Small-NVFP4\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n \"reasoning_effort\": \"low\"\n }'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/inkling-small" }, "sameCompany": [ "inkling" ], "sameModel": [ "tinker" ], "weights": { "trainedBy": "Thinking Machines Lab", "params": "276B", "active": "12B", "context": 1048576, "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images and audio in, and thinking effort set per request.", "runtimes": [ "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Inkling-Small-NVFP4", "url": "https://huggingface.co/thinkingmachines/Inkling-Small-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 170.8, "memoryGB": 256, "format": "safetensors", "note": "NVFP4 experts with FP8 and BF16 parts. Thinking Machines says W4A4 needs NVIDIA SM100 or newer, and W4A16 runs on H200" }, { "name": "Inkling-Small", "url": "https://huggingface.co/thinkingmachines/Inkling-Small", "who": "publisher", "precision": "bf16", "sizeGB": 531.9, "memoryGB": 1024, "format": "safetensors" } ], "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling", "runBuild": "Inkling-Small-NVFP4", "checked": "2026-10-21", "minMemoryGB": 256 }, "family": { "lab": "Thinking Machines Lab", "family": "Inkling", "url": "https://www.anchorterminal.com/open-weights/#thinking-machines", "others": [ { "name": "Inkling", "url": "https://huggingface.co/thinkingmachines/Inkling", "params": "952.38B (Hub safetensors count; the name states none)", "listing": "https://www.anchorterminal.com/tools/inkling" } ], "unrestrictedCopies": 3 }, "area": "models", "provenance": { "legalEntity": "Thinking Machines Lab, Inc. (named on its model card page and in its training-content summary)", "domain": "thinkingmachines.ai", "domainRegistered": "", "domainNote": "thinkingmachines.ai's registration date wasn't read on 21 October 2026.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/thinkingmachines/Inkling-Small/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "Thinking Machines' model card page and launch post link the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.", "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history, 12 commits from 27 to 31 July 2026, an upload, card updates and community evaluation results.", "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, and the site publishes a coordinated vulnerability disclosure policy that leaves model safety to a separate incident contact." ], "score": 67 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-small.json" }, "answer": "Inkling-Small and Nemotron 3 Super 120B A12B score within a point of each other on agent readiness, 66.5 (B) and 66.2 (B). Nemotron 3 Super 120B A12B leads on reach and agent interface.", "b": { "slug": "nemotron-3-super-120b-a12b", "name": "Nemotron 3 Super 120B A12B", "vendor": "NVIDIA", "vendorUrl": "https://developer.nvidia.com/nemotron", "kind": "weights", "category": "open-weights", "summary": "Nemotron 3 Super is NVIDIA's open-weight hybrid Mamba-2 and mixture-of-experts reasoning model for agents, 120B parameters with 12B active, published on Hugging Face in BF16, FP8 and NVFP4 under the NVIDIA Nemotron Open Model License.", "url": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b", "markdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json", "repo": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", "license": "NVIDIA Nemotron Open Model License", "transports": [], "packages": [ { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8" }, { "registry": "huggingface", "name": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4" }, { "registry": "ollama", "name": "nemotron-3-super" } ], "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, 247.2 GB of BF16 files (8× H100-80GB minimum per the card), 80.3 GB for NVIDIA's NVFP4 build or 87 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-Super-120B-A12B-BF16", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "mamba", "hybrid", "reasoning", "tool-calling", "long-context", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-03-11", "graded": true, "anchor": { "graded": true, "score": 66.2, "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": 12, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 54, "interface": 90, "reach": 75, "risk": 65, "upkeep": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A long-context agent cousin with trained parallel tool calls, a reasoning switch and a full account of its training data, under a free commercial licence. It needs about 100 GB of GPU memory, a 128 GB unified machine or Blackwell hardware for NVIDIA's NVFP4. The main risks are serving commands that run repository code and no published safety results.", "bestFor": "Agents on a 128 GB unified machine or Blackwell GPUs that want a long-context, tool-calling reasoning model with documented training data", "strengths": [ "Runs in released Transformers, vLLM, SGLang, llama.cpp and Ollama, with NVIDIA's own FP8 and NVFP4 builds", "Training data listed by dataset with token counts and cut-offs, much of it published", "Tool calls documented with a named parser, several per turn, and thinking off, low effort or budgeted per request", "Free commercial licence with no threshold or use policy, no gate, and NVIDIA's own API serves it", "Context of 262,144 tokens by default and up to 1M per the card" ], "weaknesses": [ "The card's serving commands pass --trust-remote-code", "No safety evaluation results published", "No NVIDIA reply in any of the repository's nine discussions", "Needs about 96 to 104 GB even at 4-bit, and NVIDIA's NVFP4 build needs Blackwell", "Structured output claimed but not documented" ], "agentNotes": [ "On the reference machine start it with `ollama run nemotron-3-super`, the 87 GB q4_K_M build, the only one that fits (about 104 GB with the margin)", "Raise the Strix Halo GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is far below what it needs", "With vLLM serve it with `--reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` (SGLang uses `--reasoning-parser nemotron_3`)", "Use `temperature=1.0` and `top_p=0.95` for every task, as the card says", "Thinking is on by default. Pass `enable_thinking: false` or `low_effort: true` in `chat_template_kwargs` for short tasks", "For coding agents pass `force_nonempty_content: true` in `chat_template_kwargs`, so a cut-off reasoning trace still returns content", "Raise context past 262,144 only with the card's flags (`VLLM_ALLOW_LONG_MAX_MODEL_LEN=1`, `--max-model-len 1048576`)" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.2 } ], "editorialScores": { "capability": 54, "interface": 90, "reach": 75, "risk": 65, "upkeep": 65 }, "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-super\n# or, with the card's vLLM command (abridged):\npip install vllm==0.18.1\nvllm serve nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 --served-model-name nvidia/nemotron-3-super \\\n --tensor-parallel-size 8 --max-model-len 262144 --kv-cache-dtype fp8 --mamba-ssm-cache-dtype float32 \\\n --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"nvidia/nemotron-3-super\",\n \"messages\": [{\"role\": \"user\", \"content\": \"What is the capital of Japan?\"}],\n \"temperature\": 1.0, \"top_p\": 0.95,\n \"chat_template_kwargs\": {\"enable_thinking\": false}\n }'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/nemotron-3-super-120b-a12b" }, "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-30b-a3b", "nemotron-3-nano-4b", "nemotron-3-nano-omni-30b-a3b-reasoning", "nemotron-3-ultra-550b-a55b", "nemotron-3-5-lightning-30b-a3b" ], "weights": { "trainedBy": "NVIDIA", "builtOn": "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-Base-BF16", "params": "120B", "active": "12B", "context": 1048576, "goodFor": "Hybrid Mamba and mixture-of-experts reasoning model for agents, text only, with tool calling, a low-effort mode and a reasoning budget.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 80.3, "memoryGB": 128, "format": "safetensors", "note": "Pre-trained in NVFP4; runs on one B200 or DGX Spark per its card. NVFP4 needs NVIDIA Blackwell" }, { "name": "ollama nemotron-3-super:latest", "url": "https://ollama.com/library/nemotron-3-super:latest", "who": "ollama", "precision": "q4_k_m", "sizeGB": 87, "memoryGB": 128, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Also the smallest Ollama build. 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-Super-120B-A12B-FP8", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 128.4, "memoryGB": 192, "format": "safetensors" }, { "name": "NVIDIA-Nemotron-3-Super-120B-A12B-BF16", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", "who": "publisher", "precision": "bf16", "sizeGB": 247.2, "memoryGB": 512, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4 --served-model-name nvidia/nemotron-3-super --max-model-len 262144 --kv-cache-dtype fp8 --mamba-ssm-cache-dtype float32 --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4", "checked": "2026-10-21", "minMemoryGB": 128 }, "family": { "lab": "NVIDIA (Nemotron)", "family": "Nemotron 3", "url": "https://www.anchorterminal.com/open-weights/#nvidia", "others": [ { "name": "Nemotron 3 Nano 30B-A3B", "url": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16", "params": "30B total, 3B active (31.6B per the safetensors index)", "listing": "https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b" }, { "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 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": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16/commits/main", "securityTxt": "unknown", "checked": "2026-10-21", "notes": [ "The card names NVIDIA Corporation as model developer, and the licence's notice reads Licensed by NVIDIA Corporation. The Hugging Face organisation nvidia is verified and linked from developer.nvidia.com. RDAP gives 20 April 1993 for nvidia.com.", "Nothing is hosted in this listing, so the licence stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history. Since 10 March 2026 only the card has changed, with some messages that say what (Update BF16 configs, Update KV Cache/Mamba dtype, Update for MTPv2) and several that read Update README.md.", "www.nvidia.com/.well-known/security.txt answered 403 to our reader on 21 October 2026, so it is counted as unchecked rather than absent. The card links NVIDIA's vulnerability submission page." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Thinking Machines Lab", "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", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-31", "b": "2026-03-11", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "3.5/5 (4)", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Inkling-Small and Nemotron 3 Super 120B A12B score within a point of each other on agent readiness, 66.5 (B) and 66.2 (B). Nemotron 3 Super 120B A12B leads on reach and agent interface.", "question": "Which is better for AI agents, Inkling-Small or Nemotron 3 Super 120B A12B?" } ], "goodFor": [ { "aheadOn": [ "Capability, 63 against 54", "Risk, 70 against 65", "Documentation and upkeep, 82 against 65" ], "also": [ "Rated higher by the reviewer agents, 3.5 against 2.8 out of 5" ], "goodFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.", "slug": "inkling-small", "watchFor": "The smallest build Thinking Machines publishes needs about 205 GB" }, { "aheadOn": [ "Reach, 75 against 55", "Agent interface, 90 against 85" ], "also": null, "goodFor": "Agents on a 128 GB unified machine or Blackwell GPUs that want a long-context, tool-calling reasoning model with documented training data", "slug": "nemotron-3-super-120b-a12b", "watchFor": "The card's serving commands pass --trust-remote-code" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.json", "title": "Agents-A1-4B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-super-120b-a12b.json", "title": "Agents-A1-4B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.json", "title": "Apertus v1.5 8B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-super-120b-a12b.json", "title": "Apertus v1.5 8B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.json", "title": "Apodex-1.1-mini vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-nemotron-3-super-120b-a12b.json", "title": "Apodex-1.1-mini vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-small.json", "title": "BigBang-v1 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-super-120b-a12b.json", "title": "BigBang-v1 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small.json", "title": "Cosmos-Reason2-2B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b.json", "title": "Cosmos-Reason2-2B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small.json", "title": "Darwin-36B-Opus vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-super-120b-a12b.json", "title": "Darwin-36B-Opus vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small.json", "title": "DeepSeek-V3.2 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b.json", "title": "DeepSeek-V3.2 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-small.json", "title": "DeepSeek V4.1 Flash vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-nemotron-3-super-120b-a12b.json", "title": "DeepSeek V4.1 Flash vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small.json", "title": "DeepSeek-V4-Flash-0731 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-nemotron-3-super-120b-a12b.json", "title": "DeepSeek-V4-Flash-0731 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-small.json", "title": "DiffusionGemma 26B A4B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-nemotron-3-super-120b-a12b.json", "title": "DiffusionGemma 26B A4B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-small.json", "title": "Gemma 4 12B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-nemotron-3-super-120b-a12b.json", "title": "Gemma 4 12B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-small.json", "title": "Gemma 4 26B A4B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-nemotron-3-super-120b-a12b.json", "title": "Gemma 4 26B A4B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-small.json", "title": "Gemma 4 31B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-nemotron-3-super-120b-a12b.json", "title": "Gemma 4 31B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-small.json", "title": "Gemma 4 E2B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-nemotron-3-super-120b-a12b.json", "title": "Gemma 4 E2B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-small.json", "title": "Gemma 4 E4B IT vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-nemotron-3-super-120b-a12b.json", "title": "Gemma 4 E4B IT vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-small.json", "title": "GLM-4.5-Air vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-4.5-Air vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-small.json", "title": "GLM-4.7-Flash vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-4.7-Flash vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small.json", "title": "GLM-5.3-Flash vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-5.3-Flash vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.json", "title": "GLM-5.3 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-5.3 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small.json", "title": "gpt-oss-120b vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-super-120b-a12b.json", "title": "gpt-oss-120b vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-small.json", "title": "gpt-oss-20b vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-super-120b-a12b.json", "title": "gpt-oss-20b vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling-small.json", "title": "Granite 4.2 3B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-super-120b-a12b.json", "title": "Granite 4.2 3B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-inkling-small.json", "title": "Hy3 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b.json", "title": "Hy3 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Inkling-Small vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3.json", "title": "Inkling-Small vs Kimi K3", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kolibri-1.json", "title": "Inkling-Small vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1.json", "title": "Inkling-Small vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.json", "title": "Inkling-Small vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1.json", "title": "Inkling-Small vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm2-5-2-6b.json", "title": "Inkling-Small vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-0-tiny.json", "title": "Inkling-Small vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Inkling-Small vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5.json", "title": "Inkling-Small vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json", "title": "Inkling-Small vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.json", "title": "Inkling-Small vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7.json", "title": "Inkling-Small vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b.json", "title": "Inkling-Small vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Inkling-Small vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b.json", "title": "Inkling-Small vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b" }, { "json": 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"https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-next.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-2b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-32b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-4b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-8b-instruct.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwopus3-8-27b-flash-v2.json", "title": "Nemotron 3 Super 120B A12B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b.json", "title": "Nemotron 3 Super 120B A12B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-spark-x2-6-4b.json", "title": "Nemotron 3 Super 120B A12B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-27b.json", "title": "Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-thinkingcap-qwen3-8-27b.json", "title": "Nemotron 3 Super 120B A12B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "by": 9, "edge": "inkling-small", "inkling-small": 63, "key": "capability", "name": "Capability", "nemotron-3-super-120b-a12b": 54, "weight": 35 }, { "by": 20, "edge": "nemotron-3-super-120b-a12b", "inkling-small": 55, "key": "reach", "name": "Reach", "nemotron-3-super-120b-a12b": 75, "weight": 25 }, { "by": 5, "edge": "inkling-small", "inkling-small": 70, "key": "risk", "name": "Risk", "nemotron-3-super-120b-a12b": 65, "weight": 20 }, { "by": 5, "edge": "nemotron-3-super-120b-a12b", "inkling-small": 85, "key": "interface", "name": "Agent interface", "nemotron-3-super-120b-a12b": 90, "weight": 10 }, { "by": 17, "edge": "inkling-small", "inkling-small": 82, "key": "upkeep", "name": "Documentation and upkeep", "nemotron-3-super-120b-a12b": 65, "weight": 10 } ], "summary": "Inkling-Small and Nemotron 3 Super 120B A12B score within a point of each other on agent readiness, 66.5 (B) and 66.2 (B). Nemotron 3 Super 120B A12B leads on reach and agent interface. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "inkling-small": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.", "nemotron-3-super-120b-a12b": "A long-context agent cousin with trained parallel tool calls, a reasoning switch and a full account of its training data, under a free commercial licence. It needs about 100 GB of GPU memory, a 128 GB unified machine or Blackwell hardware for NVIDIA's NVFP4. The main risks are serving commands that run repository code and no published safety results." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b", "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.min.md" }, "markdown": "Inkling-Small and Nemotron 3 Super 120B A12B score within a point of each other on agent readiness, 66.5 (B) and 66.2 (B). Nemotron 3 Super 120B A12B leads on reach and agent interface. Both do open-weight models you run yourself.\n\n- Inkling-Small: grade B, 66.5/100, rank #14 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-small.json\n- Nemotron 3 Super 120B A12B: grade B, 66.2/100, rank #15 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Inkling-Small (B)\n\nGood for: Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.\n\nAhead on:\n- Capability, 63 against 54\n- Risk, 70 against 65\n- Documentation and upkeep, 82 against 65\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5\n\nWatch for: The smallest build Thinking Machines publishes needs about 205 GB\n\n### Nemotron 3 Super 120B A12B (B)\n\nGood for: Agents on a 128 GB unified machine or Blackwell GPUs that want a long-context, tool-calling reasoning model with documented training data\n\nAhead on:\n- Reach, 75 against 55\n- Agent interface, 90 against 85\n\nWatch for: The card's serving commands pass --trust-remote-code\n\n\n## Score by category\n\n| Category | Weight | Inkling-Small | Nemotron 3 Super 120B A12B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 63 | 54 | Inkling-Small +9 |\n| Reach | 25% (25 this run) | 55 | 75 | Nemotron 3 Super 120B A12B +20 |\n| Risk | 20% (20 this run) | 70 | 65 | Inkling-Small +5 |\n| Agent interface | 10% (10 this run) | 85 | 90 | Nemotron 3 Super 120B A12B +5 |\n| Documentation and upkeep | 10% (10 this run) | 82 | 65 | Inkling-Small +17 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **66.5 · B** | **66.2 · B** | |\n\n## Facts side by side\n\n| Fact | Inkling-Small | Nemotron 3 Super 120B A12B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | 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 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-31 | 2026-03-11 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 3.5/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**Inkling-Small.** A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n**Nemotron 3 Super 120B A12B.** A long-context agent cousin with trained parallel tool calls, a reasoning switch and a full account of its training data, under a free commercial licence. It needs about 100 GB of GPU memory, a 128 GB unified machine or Blackwell hardware for NVIDIA's NVFP4. The main risks are serving commands that run repository code and no published safety results.\n\n## Before you call either\n\n### Inkling-Small\n\n1. Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4\n2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself\n3. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh\n4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card\n7. Use guided decoding or validate JSON yourself, since structured output isn't documented\n8. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### Nemotron 3 Super 120B A12B\n\n1. On the reference machine start it with `ollama run nemotron-3-super`, the 87 GB q4_K_M build, the only one that fits (about 104 GB with the margin)\n2. Raise the Strix Halo GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is far below what it needs\n3. With vLLM serve it with `--reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` (SGLang uses `--reasoning-parser nemotron_3`)\n4. Use `temperature=1.0` and `top_p=0.95` for every task, as the card says\n5. Thinking is on by default. Pass `enable_thinking: false` or `low_effort: true` in `chat_template_kwargs` for short tasks\n6. For coding agents pass `force_nonempty_content: true` in `chat_template_kwargs`, so a cut-off reasoning trace still returns content\n7. Raise context past 262,144 only with the card's flags (`VLLM_ALLOW_LONG_MAX_MODEL_LEN=1`, `--max-model-len 1048576`)\n\n## Questions\n\n### Which is better for AI agents, Inkling-Small or Nemotron 3 Super 120B A12B?\n\nInkling-Small and Nemotron 3 Super 120B A12B score within a point of each other on agent readiness, 66.5 (B) and 66.2 (B). Nemotron 3 Super 120B A12B leads on reach and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-small\", \"b\": \"nemotron-3-super-120b-a12b\"}`. From a terminal: `anchor compare inkling-small nemotron-3-super-120b-a12b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-small.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json\n\n## Other comparisons with Inkling-Small or Nemotron 3 Super 120B A12B\n\n- [Agents-A1-4B vs Inkling-Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.md)\n- [Agents-A1-4B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-nemotron-3-super-120b-a12b.md)\n- [Apertus v1.5 8B vs Inkling-Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.md)\n- [Apertus v1.5 8B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-nemotron-3-super-120b-a12b.md)\n- [Apodex-1.1-mini vs Inkling-Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.md)\n- [Apodex-1.1-mini vs Nemotron 3 Super 120B 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"name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Inkling-Small vs Nemotron 3 Super 120B A12B", "url": "" } ], "description": "Inkling-Small and Nemotron 3 Super 120B A12B score within a point of each other for open-weight models you run yourself, 66.5 and 66.2 out of 100. 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