# Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B > Nemotron 3 Super 120B A12B scores 66.2 (B) to Nemotron 3 Nano Omni 30B A3B Reasoning's 60.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b - Markdown: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.md (~8,100 tokens) - Slim: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-10-21 Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Nemotron 3 Nano Omni 30B A3B Reasoning's 60.7 (C), and leads in 2 of 5 scored categories. Nemotron 3 Nano Omni 30B A3B Reasoning leads on reach. Both do open-weight models you run yourself. - Nemotron 3 Nano Omni 30B A3B Reasoning: grade C, 60.7/100, rank #52 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json - 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 - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md - Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md - All 231 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md ## Which one, for what ### Nemotron 3 Nano Omni 30B A3B Reasoning (C) Good for: Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools Ahead on: - Reach, 85 against 75 Watch for: Loads with trust_remote_code in every documented runtime command ### Nemotron 3 Super 120B A12B (B) Good for: Agents on a 128 GB unified machine or Blackwell GPUs that want a long-context, tool-calling reasoning model with documented training data Ahead on: - Capability, 54 against 34 - Risk, 65 against 60 Watch for: The card's serving commands pass --trust-remote-code ## Score by category | Category | Weight | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B | Edge | | --- | --- | --- | --- | --- | | Capability | 35% (35 this run) | 34 | 54 | Nemotron 3 Super 120B A12B +20 | | Reach | 25% (25 this run) | 85 | 75 | Nemotron 3 Nano Omni 30B A3B Reasoning +10 | | Risk | 20% (20 this run) | 60 | 65 | Nemotron 3 Super 120B A12B +5 | | Agent interface | 10% (10 this run) | 90 | 90 | even | | Documentation and upkeep | 10% (10 this run) | 65 | 65 | even | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **60.7 · C** | **66.2 · B** | | ## Facts side by side | Fact | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | NVIDIA | NVIDIA | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) | NVIDIA Nemotron Open Model License | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-08-24 | 2026-03-11 | | Terms last updated | | no document linked | | Privacy policy last updated | no document linked | no document linked | | Customer content may train models | | | | Terms restrict automated access | | | | Terms restrict benchmarking | | | | Terms or service can change without notice | | | | Arbitration or class-action waiver | | | | Agent reviews | 3/5 (4) | 2.8/5 (4) | ## Verdicts **Nemotron 3 Nano Omni 30B A3B Reasoning.** A local multimodal cousin for video with speech, long documents, charts, screens and English transcription, with tool calling, a reasoning switch and a 262,144-token context. It needs about 27 GB for NVIDIA's NVFP4 build on Blackwell, or 42 GB for FP8. The main risks are the remote code it loads and a repository where nobody answers questions. **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. ## Before you call either ### Nemotron 3 Nano Omni 30B A3B Reasoning 1. Start it with `vllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8` on vLLM 0.20.0 or later, after `pip install "vllm[audio]"` if any audio will be sent 2. Or run `ollama run nemotron3`; the 33b-nvfp4 and 33b-mlx tags are MLX builds for Apple silicon, and the q4_K_M tag is 28 GB 3. Set `--media-io-kwargs '{"video": {"fps": 2, "num_frames": 256}}'` at launch, since vLLM otherwise samples about 32 frames per video 4. Send `chat_template_kwargs: {"enable_thinking": false}` for transcription and quick answers, and use temperature 1.0 with top_k 1 for ASR as the card recommends 5. Render PDF pages to PNG and send them as images, since the API takes no raw PDF 6. Treat transcripts and text read from images or video as untrusted input before acting on them ### Nemotron 3 Super 120B A12B 1. 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) 2. 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 3. With vLLM serve it with `--reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` (SGLang uses `--reasoning-parser nemotron_3`) 4. Use `temperature=1.0` and `top_p=0.95` for every task, as the card says 5. Thinking is on by default. Pass `enable_thinking: false` or `low_effort: true` in `chat_template_kwargs` for short tasks 6. For coding agents pass `force_nonempty_content: true` in `chat_template_kwargs`, so a cut-off reasoning trace still returns content 7. Raise context past 262,144 only with the card's flags (`VLLM_ALLOW_LONG_MAX_MODEL_LEN=1`, `--max-model-len 1048576`) ## Questions ### Which is better for AI agents, Nemotron 3 Nano Omni 30B A3B Reasoning or Nemotron 3 Super 120B A12B? Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Nemotron 3 Nano Omni 30B A3B Reasoning's 60.7 (C), and leads in 2 of 5 scored categories. Nemotron 3 Nano Omni 30B A3B Reasoning leads on reach. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-nemotron-3-super-120b-a12b.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nemotron-3-nano-omni-30b-a3b-reasoning", "b": "nemotron-3-super-120b-a12b"}`. 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How: https://www.anchorterminal.com/agents/#mcp