{ "data": { "a": { "slug": "ling-3-0-tiny", "name": "Ling-3.0-tiny", "vendor": "inclusionAI (Ant Group)", "vendorUrl": "https://www.inclusion-ai.org", "kind": "weights", "category": "open-weights", "summary": "Ling-3.0-tiny is inclusionAI's open-weight hybrid reasoning mixture of experts with 7.9B parameters and 1.3B active, mixing Kimi Delta Attention and MLA layers 3 to 1, with switchable thinking and a 131,072-token context, in BF16, FP8, INT4 and GGUF under MIT.", "url": "https://www.anchorterminal.com/tools/ling-3-0-tiny", "markdownUrl": "https://www.anchorterminal.com/tools/ling-3-0-tiny.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ling-3-0-tiny.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ling-3-0-tiny.json", "repo": "https://huggingface.co/inclusionAI/Ling-3.0-tiny", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "inclusionAI/Ling-3.0-tiny" }, { "registry": "huggingface", "name": "inclusionAI/Ling-3.0-tiny-fp8" }, { "registry": "huggingface", "name": "inclusionAI/Ling-3.0-tiny-int4" }, { "registry": "huggingface", "name": "inclusionAI/Ling-3.0-tiny-GGUF" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the four repositories is gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under MIT (named in the card's metadata; the repositories hold no LICENSE file). Running it yourself costs the hardware, 15.8 GB for the BF16 files, 8.4 GB for the FP8 build, 5.8 GB for INT4 and 4.8 GB for the Q4_K_M GGUF (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/inclusionAI/Ling-3.0-tiny", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "hybrid-attention", "reasoning", "tool-calling", "mit", "safetensors", "fp8", "int4", "gguf", "self-hosted" ], "lastRelease": "2026-08-31", "graded": true, "anchor": { "graded": true, "score": 55, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 65, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 31, "interface": 60, "reach": 90, "risk": 50, "upkeep": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A small, quick hybrid reasoning cousin for local agent work, tool calls and coding, under MIT. It runs in about 6 GB from inclusionAI's 4-bit GGUF in released Transformers, vLLM, SGLang and llama.cpp, with no host. The main risks are a card that doesn't match the files in places, the vLLM route running repository code, and no model safety results.", "bestFor": "Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT", "strengths": [ "About 6 GB of memory for inclusionAI's own Q4_K_M GGUF, with FP8, INT4 and three more GGUF precisions", "Runs in released Transformers, vLLM, SGLang and llama.cpp", "MIT with no gate, no account and no use policy, with checksummed files in inclusionAI's own organisation", "Thinking switchable per request, several tool calls a turn and 131,072 tokens of native context", "A training-content summary with sources, size and an October 2025 cut-off, and a guardrail probe made for this model" ], "weaknesses": [ "No hosted provider today, and Ollama support is only an unmerged pull request", "The card's SGLang recipe asks for built-in MTP the files don't have, and the safetensors index misstates the total size", "The documented vLLM route needs --trust-remote-code", "No safety results for the model, no structured output and no security contact", "Card and SGLang disagree on which tool and reasoning parsers to use, and most discussions since August have no reply" ], "agentNotes": [ "Start it with `llama-server -hf inclusionAI/Ling-3.0-tiny-GGUF:Q4_K_M --jinja -c 32768`, which needs llama.cpp b11772 or a recent release with bailingmoe3", "With vLLM 0.32.0, `vllm serve inclusionAI/Ling-3.0-tiny --trust-remote-code --enable-prefix-caching --mamba-cache-mode align --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3`, which runs the repository's config code", "With SGLang 0.5.22, its cookbook uses `--reasoning-parser deepseek-r1 --tool-call-parser glm45` for this model, and drop the card's NEXTN flags since tiny has no MTP layer", "Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false for short tasks", "Sampling per the card is temperature 1.0, top_p 0.95 and top_k 20", "The template keeps earlier reasoning in the prompt, which grows long agent sessions", "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented", "For a guardrail, inclusionAI's Ling-3.0-tiny-singprobe scores intent, unsafe output and hallucination per token, but only through SGLang and vLLM integration branches" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55 } ], "editorialScores": { "capability": 31, "interface": 60, "reach": 90, "risk": 50, "upkeep": 56 }, "provenanceScore": 57, "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": "llama-server -hf inclusionAI/Ling-3.0-tiny-GGUF:Q4_K_M --jinja -c 32768\n# or with vLLM 0.32.0, per the card's serve command:\nvllm serve inclusionAI/Ling-3.0-tiny --trust-remote-code --enable-prefix-caching --mamba-cache-mode align \\\n --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"inclusionAI/Ling-3.0-tiny\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"enable_thinking\": false}, \"temperature\": 1.0, \"top_p\": 0.95, \"top_k\": 20}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/ling-3-0-tiny" }, "sameCompany": [ "ming-3-0-asr-tiny", "ming-3-0-audio-flash", "ming-3-0-audio-tiny", "ming-3-0-tts-tiny" ], "weights": { "trainedBy": "inclusionAI (Ant Group)", "params": "7.9B (1.3B active)", "context": 131072, "goodFor": "Small, fast hybrid reasoning model for local agents, tool calling and coding on a laptop, with thinking switchable per request.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Ling-3.0-tiny-int4", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-int4", "who": "publisher", "precision": "int4", "sizeGB": 5.8, "memoryGB": 8, "format": "safetensors", "note": "compressed-tensors, 4-bit weights in groups of 32, with attention and dense layers kept at higher precision" }, { "name": "Ling-3.0-tiny-Q6_K", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-GGUF/blob/main/Ling-3.0-tiny-Q6_K.gguf", "who": "publisher", "precision": "q6_k", "sizeGB": 6.5, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "Ling-3.0-tiny-Q5_K_M", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-GGUF/blob/main/Ling-3.0-tiny-Q5_K_M.gguf", "who": "publisher", "precision": "q5_k_m", "sizeGB": 5.6, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "Ling-3.0-tiny-Q4_K_M", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-GGUF/blob/main/Ling-3.0-tiny-Q4_K_M.gguf", "who": "publisher", "precision": "q4_k_m", "sizeGB": 4.8, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "Ling-3.0-tiny-fp8", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-fp8", "who": "publisher", "precision": "fp8", "sizeGB": 8.4, "memoryGB": 12, "format": "safetensors" }, { "name": "Ling-3.0-tiny-Q8_0", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-GGUF/blob/main/Ling-3.0-tiny-Q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 8.4, "memoryGB": 12, "format": "gguf", "runsOn": [ "llama.cpp" ] }, { "name": "Ling-3.0-tiny", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny", "who": "publisher", "precision": "bf16", "sizeGB": 15.8, "memoryGB": 24, "format": "safetensors" } ], "run": "llama-server -hf inclusionAI/Ling-3.0-tiny-GGUF:Q4_K_M --jinja -c 32768", "runBuild": "Ling-3.0-tiny-Q4_K_M", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "inclusionAI (Ant Group)", "family": "Ling 3", "url": "https://www.anchorterminal.com/open-weights/#inclusionai", "others": [ { "name": "Ling-3.0-flash", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base-30T", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-30T", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base-midtrain", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-midtrain", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-Fin", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-VL", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-VL", "params": "124B total, 5.5B active" }, { "name": "Ling-3.0-flash-dspark", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-dspark", "params": "1.36B (draft)" }, { "name": "Ling-3.0-flash-singprobe", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-singprobe", "params": "5.18M (probe)" }, { "name": "Ling-3.0-tiny-base", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-base-30T", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-30T", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-base-midtrain", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-midtrain", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-singprobe", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-singprobe", "params": "3.22M (probe)" }, { "name": "Ling-3.1-flash", "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash", "params": "560B total, 25B active" } ], "olderCount": 54, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Ant Intelligence (Hang Zhou) Technology Co., Ltd (named as provider in the training-content summary); inclusionAI, Ant Group in the site footer of inclusion-ai.org", "domain": "inclusion-ai.org", "domainRegistered": "2025-04-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/inclusionAI/Ling-3.0-tiny/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI. The domain registration date is carried from the RDAP check made for the Ming 3.0 listings on 21 October 2026.", "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the Hugging Face commit history, 17 commits from 10 August to 24 September 2026, mostly README updates, the last adding the training-content summary.", "inclusion-ai.org/.well-known/security.txt answered 404 on 21 October 2026, and the inclusionAI .github repository holds only a profile README." ], "score": 57 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ling-3-0-tiny.json" }, "answer": "Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Ling-3.0-tiny leads on reach.", "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": "inclusionAI (Ant Group)", "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": "MIT", "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": "2026-08-31", "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": "2.8/5 (4)", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Ling-3.0-tiny leads on reach.", "question": "Which is better for AI agents, Ling-3.0-tiny or Nemotron 3 Super 120B A12B?" } ], "goodFor": [ { "aheadOn": [ "Reach, 90 against 75" ], "also": null, "goodFor": "Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT", "slug": "ling-3-0-tiny", "watchFor": "No hosted provider today, and Ollama support is only an unmerged pull request" }, { "aheadOn": [ "Capability, 54 against 31", "Risk, 65 against 50", "Agent interface, 90 against 60", "Documentation and upkeep, 65 against 56" ], "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-ling-3-0-tiny.json", "title": "Agents-A1-4B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Apertus v1.5 8B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Apodex-1.1-mini vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "BigBang-v1 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Cosmos-Reason2-2B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Darwin-36B-Opus vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "DeepSeek-V3.2 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "DeepSeek V4.1 Flash vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "DeepSeek-V4-Flash-0731 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "DiffusionGemma 26B A4B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Gemma 4 12B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Gemma 4 26B A4B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Gemma 4 31B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Gemma 4 E2B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Gemma 4 E4B IT vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "GLM-4.5-Air vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "GLM-4.7-Flash vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "GLM-5.3-Flash vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "GLM-5.3 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "gpt-oss-120b vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "gpt-oss-20b vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": "Granite 4.2 3B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ling-3-0-tiny" }, { "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-ling-3-0-tiny.json", "title": 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}, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-397b.json", "title": "Ling-3.0-tiny vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-9b.json", "title": "Ling-3.0-tiny vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Ling-3.0-tiny vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-4b-instruct-2507.json", "title": "Ling-3.0-tiny vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-4b-instruct-2507" }, { "json": 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A12B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-nemotron-3-ultra-550b-a55b.json", "title": "Nemotron 3 Super 120B A12B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0.json", "title": "Nemotron 3 Super 120B A12B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0" }, { "json": 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"https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-4b-instruct-2507.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-0-8b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-122b-a10b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-397b-a17b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-4b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-9b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-35b-a3b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-27b.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-flash-next.json", "title": "Nemotron 3 Super 120B A12B vs Qwen3.8-Flash-Next", "url": "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": 23, "edge": "nemotron-3-super-120b-a12b", "key": "capability", "ling-3-0-tiny": 31, "name": "Capability", "nemotron-3-super-120b-a12b": 54, "weight": 35 }, { "by": 15, "edge": "ling-3-0-tiny", "key": "reach", "ling-3-0-tiny": 90, "name": "Reach", "nemotron-3-super-120b-a12b": 75, "weight": 25 }, { "by": 15, "edge": "nemotron-3-super-120b-a12b", "key": "risk", "ling-3-0-tiny": 50, "name": "Risk", "nemotron-3-super-120b-a12b": 65, "weight": 20 }, { "by": 30, "edge": "nemotron-3-super-120b-a12b", "key": "interface", "ling-3-0-tiny": 60, "name": "Agent interface", "nemotron-3-super-120b-a12b": 90, "weight": 10 }, { "by": 9, "edge": "nemotron-3-super-120b-a12b", "key": "upkeep", "ling-3-0-tiny": 56, "name": "Documentation and upkeep", "nemotron-3-super-120b-a12b": 65, "weight": 10 } ], "summary": "Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Ling-3.0-tiny leads on reach. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "ling-3-0-tiny": "A small, quick hybrid reasoning cousin for local agent work, tool calls and coding, under MIT. It runs in about 6 GB from inclusionAI's 4-bit GGUF in released Transformers, vLLM, SGLang and llama.cpp, with no host. The main risks are a card that doesn't match the files in places, the vLLM route running repository code, and no model 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/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b", "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.min.md" }, "markdown": "Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Ling-3.0-tiny leads on reach. Both do open-weight models you run yourself.\n\n- Ling-3.0-tiny: grade C, 55/100, rank #81 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/ling-3-0-tiny.md · JSON https://www.anchorterminal.com/api/v1/tools/ling-3-0-tiny.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### Ling-3.0-tiny (C)\n\nGood for: Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT\n\nAhead on:\n- Reach, 90 against 75\n\nWatch for: No hosted provider today, and Ollama support is only an unmerged pull request\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- Capability, 54 against 31\n- Risk, 65 against 50\n- Agent interface, 90 against 60\n- Documentation and upkeep, 65 against 56\n\nWatch for: The card's serving commands pass --trust-remote-code\n\n\n## Score by category\n\n| Category | Weight | Ling-3.0-tiny | Nemotron 3 Super 120B A12B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 31 | 54 | Nemotron 3 Super 120B A12B +23 |\n| Reach | 25% (25 this run) | 90 | 75 | Ling-3.0-tiny +15 |\n| Risk | 20% (20 this run) | 50 | 65 | Nemotron 3 Super 120B A12B +15 |\n| Agent interface | 10% (10 this run) | 60 | 90 | Nemotron 3 Super 120B A12B +30 |\n| Documentation and upkeep | 10% (10 this run) | 56 | 65 | Nemotron 3 Super 120B A12B +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55 · C** | **66.2 · B** | |\n\n## Facts side by side\n\n| Fact | Ling-3.0-tiny | Nemotron 3 Super 120B A12B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | inclusionAI (Ant Group) | 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 | MIT | NVIDIA Nemotron Open Model License |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-31 | 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 | 2.8/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**Ling-3.0-tiny.** A small, quick hybrid reasoning cousin for local agent work, tool calls and coding, under MIT. It runs in about 6 GB from inclusionAI's 4-bit GGUF in released Transformers, vLLM, SGLang and llama.cpp, with no host. The main risks are a card that doesn't match the files in places, the vLLM route running repository code, and no model 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### Ling-3.0-tiny\n\n1. Start it with `llama-server -hf inclusionAI/Ling-3.0-tiny-GGUF:Q4_K_M --jinja -c 32768`, which needs llama.cpp b11772 or a recent release with bailingmoe3\n2. With vLLM 0.32.0, `vllm serve inclusionAI/Ling-3.0-tiny --trust-remote-code --enable-prefix-caching --mamba-cache-mode align --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3`, which runs the repository's config code\n3. With SGLang 0.5.22, its cookbook uses `--reasoning-parser deepseek-r1 --tool-call-parser glm45` for this model, and drop the card's NEXTN flags since tiny has no MTP layer\n4. Thinking is on by default, pass `chat_template_kwargs` with `enable_thinking` false for short tasks\n5. Sampling per the card is temperature 1.0, top_p 0.95 and top_k 20\n6. The template keeps earlier reasoning in the prompt, which grows long agent sessions\n7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n8. For a guardrail, inclusionAI's Ling-3.0-tiny-singprobe scores intent, unsafe output and hallucination per token, but only through SGLang and vLLM integration branches\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, Ling-3.0-tiny or Nemotron 3 Super 120B A12B?\n\nNemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Ling-3.0-tiny's 55 (C), and leads in 4 of 5 scored categories. Ling-3.0-tiny leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ling-3-0-tiny\", \"b\": \"nemotron-3-super-120b-a12b\"}`. From a terminal: `anchor compare ling-3-0-tiny nemotron-3-super-120b-a12b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ling-3-0-tiny.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json\n\n## Other comparisons with Ling-3.0-tiny or Nemotron 3 Super 120B A12B\n\n- [Agents-A1-4B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-0-tiny.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 Ling-3.0-tiny](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-0-tiny.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 Ling-3.0-tiny](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-0-tiny.md)\n- [Apodex-1.1-mini vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-nemotron-3-super-120b-a12b.md)\n- [BigBang-v1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-0-tiny.md)\n- [BigBang-v1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-super-120b-a12b.md)\n- [Cosmos-Reason2-2B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny.md)\n- [Cosmos-Reason2-2B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b.md)\n- [Darwin-36B-Opus vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ling-3-0-tiny.md)\n- [Darwin-36B-Opus vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-nemotron-3-super-120b-a12b.md)\n- [DeepSeek-V3.2 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-0-tiny.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b.md)\n- [DeepSeek V4.1 Flash vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ling-3-0-tiny.md)\n- [DeepSeek V4.1 Flash vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-nemotron-3-super-120b-a12b.md)\n- [DeepSeek-V4-Flash-0731 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ling-3-0-tiny.md)\n- [DeepSeek-V4-Flash-0731 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-nemotron-3-super-120b-a12b.md)\n- [DiffusionGemma 26B A4B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ling-3-0-tiny.md)\n- [DiffusionGemma 26B A4B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-nemotron-3-super-120b-a12b.md)\n- [Gemma 4 12B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ling-3-0-tiny.md)\n- [Gemma 4 12B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-nemotron-3-super-120b-a12b.md)\n- [Gemma 4 26B A4B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ling-3-0-tiny.md)\n- [Gemma 4 26B A4B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-nemotron-3-super-120b-a12b.md)\n- [Gemma 4 31B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ling-3-0-tiny.md)\n- [Gemma 4 31B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-nemotron-3-super-120b-a12b.md)\n- [Gemma 4 E2B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ling-3-0-tiny.md)\n- [Gemma 4 E2B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-nemotron-3-super-120b-a12b.md)\n- [Gemma 4 E4B IT vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ling-3-0-tiny.md)\n- [Gemma 4 E4B IT vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-4.5-Air vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-4-5-air-vs-ling-3-0-tiny.md)\n- [GLM-4.5-Air vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-4.7-Flash vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ling-3-0-tiny.md)\n- [GLM-4.7-Flash vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-5.3-Flash vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-0-tiny.md)\n- [GLM-5.3-Flash vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-5.3 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny.md)\n- [GLM-5.3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.md)\n- [gpt-oss-120b vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ling-3-0-tiny.md)\n- [gpt-oss-120b vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-nemotron-3-super-120b-a12b.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 Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-nemotron-3-super-120b-a12b.md)\n- [Granite 4.2 3B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ling-3-0-tiny.md)\n- [Granite 4.2 3B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-super-120b-a12b.md)\n- [Hy3 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/hy3-vs-ling-3-0-tiny.md)\n- [Hy3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b.md)\n- [Inkling-Small vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/inkling-small-vs-ling-3-0-tiny.md)\n- [Inkling-Small vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.md)\n- [Inkling vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/inkling-vs-ling-3-0-tiny.md)\n- [Inkling vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/inkling-vs-nemotron-3-super-120b-a12b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ling-3-0-tiny.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-nemotron-3-super-120b-a12b.md)\n- [Kimi K3 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-0-tiny.md)\n- [Kimi K3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-super-120b-a12b.md)\n- [Kolibri-1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/kolibri-1-vs-ling-3-0-tiny.md)\n- [Kolibri-1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/kolibri-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna M.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-0-tiny.md)\n- [Laguna M.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna S 2.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-0-tiny.md)\n- [Laguna S 2.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna XS 2.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-0-tiny.md)\n- [Laguna XS 2.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-super-120b-a12b.md)\n- [LFM2.5-2.6B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ling-3-0-tiny.md)\n- [LFM2.5-2.6B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-nemotron-3-super-120b-a12b.md)\n- [Ling-3.0-tiny vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Ling-3.0-tiny vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm-o-4-5.md)\n- [Ling-3.0-tiny vs MiniCPM5-2B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minicpm5-2b.md)\n- [Ling-3.0-tiny vs MiniMax-M2.5](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minimax-m2-5.md)\n- [Ling-3.0-tiny vs MiniMax-M2.7](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-minimax-m2-7.md)\n- [Ling-3.0-tiny vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-muse-glimmer-30b.md)\n- [Ling-3.0-tiny vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-5-lightning-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- [Ling-3.0-tiny vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-nano-4b.md)\n- [Ling-3.0-tiny vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Ling-3.0-tiny vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-ultra-550b-a55b.md)\n- [Ling-3.0-tiny vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.md)\n- [Ling-3.0-tiny vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-olmo-3-7b-think.md)\n- [Ling-3.0-tiny vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-35b-a3b.md)\n- [Ling-3.0-tiny vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-397b.md)\n- [Ling-3.0-tiny vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-9b.md)\n- [Ling-3.0-tiny vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Ling-3.0-tiny vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-4b-instruct-2507.md)\n- [Ling-3.0-tiny vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-0-8b.md)\n- [Ling-3.0-tiny vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-122b-a10b.md)\n- [Ling-3.0-tiny vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-2b.md)\n- [Ling-3.0-tiny vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-397b-a17b.md)\n- [Ling-3.0-tiny vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-4b.md)\n- [Ling-3.0-tiny vs Qwen3.5-9B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-5-9b.md)\n- [Ling-3.0-tiny vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-6-27b.md)\n- [Ling-3.0-tiny vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-6-35b-a3b.md)\n- [Ling-3.0-tiny vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-8-27b.md)\n- [Ling-3.0-tiny vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-8-flash-next.md)\n- [Ling-3.0-tiny vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-coder-next.md)\n- [Ling-3.0-tiny vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-2b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-32b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-4b-instruct.md)\n- [Ling-3.0-tiny vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-vl-8b-instruct.md)\n- [Ling-3.0-tiny vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwopus3-8-27b-flash-v2.md)\n- [Ling-3.0-tiny vs SmolLM3-3B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-smollm3-3b.md)\n- [Ling-3.0-tiny vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-spark-x2-6-4b.md)\n- [Ling-3.0-tiny vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-swift-1-5-qwen3-8-27b.md)\n- [Ling-3.0-tiny vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ling-3.0-tiny vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-thinkingcap-qwen3-8-27b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-super-120b-a12b.md)\n- [MiniCPM-o 4.5 vs Nemotron 3 Super 120B 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"name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Ling-3.0-tiny vs Nemotron 3 Super 120B A12B", "url": "" } ], "description": "Nemotron 3 Super 120B A12B scores 66.2 (B) to Ling-3.0-tiny's 55 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Ling-3.0-tiny C 55", "Nemotron 3 Super 120B A12B B 66.2", "scores" ], "h1": "Ling-3.0-tiny vs Nemotron 3 Super 120B A12B", "image": "https://www.anchorterminal.com/assets/og/compare-ling-3-0-tiny-vs-nemotron-3-super-120b-a12b.png", "path": "/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b", "published": "2026-10-01", "section": "tools", "title": "Ling-3.0-tiny vs Nemotron 3 Super 120B A12B for AI agents (2026)", "toc": null, "updated": "2026-10-21", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-nemotron-3-super-120b-a12b" }, "tokens": { "markdown": 6650, "slim": 480 }, "version": 1 }