# DeepSeek-V3.2 vs Nemotron 3 Nano Omni 30B A3B Reasoning

> Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) to DeepSeek-V3.2's 58.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning
- Markdown: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md (~7,600 tokens)
- Slim: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.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 Nano Omni 30B A3B Reasoning scores 60.7 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 4 of 5 scored categories. DeepSeek-V3.2 leads on capability. Both do open-weight models you run yourself.

- DeepSeek-V3.2: grade C, 58.6/100, rank #65 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/deepseek-v3-2.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json
- 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
- 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

### DeepSeek-V3.2 (C)

Good for: Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider

Ahead on:
- Capability, 69 against 34

Watch for: 689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB

### 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 60
- Risk, 60 against 50
- Agent interface, 90 against 60
- Documentation and upkeep, 65 against 34

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.3 out of 5

Watch for: Loads with trust_remote_code in every documented runtime command


## Score by category

| Category | Weight | DeepSeek-V3.2 | Nemotron 3 Nano Omni 30B A3B Reasoning | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 69 | 34 | DeepSeek-V3.2 +35 |
| Reach | 25% (25 this run) | 60 | 85 | Nemotron 3 Nano Omni 30B A3B Reasoning +25 |
| Risk | 20% (20 this run) | 50 | 60 | Nemotron 3 Nano Omni 30B A3B Reasoning +10 |
| Agent interface | 10% (10 this run) | 60 | 90 | Nemotron 3 Nano Omni 30B A3B Reasoning +30 |
| Documentation and upkeep | 10% (10 this run) | 34 | 65 | Nemotron 3 Nano Omni 30B A3B Reasoning +31 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **58.6 · C** | **60.7 · C** | |

## Facts side by side

| Fact | DeepSeek-V3.2 | Nemotron 3 Nano Omni 30B A3B Reasoning |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | DeepSeek | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-12-01 | 2026-08-24 |
| 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 | 2.3/5 (4) | 3/5 (4) |

## Verdicts

**DeepSeek-V3.2.** DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.

**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.

## Before you call either

### DeepSeek-V3.2

1. Start it with vLLM's recipe, vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3
2. It doesn't fit the 107.4 GB reference machine at any qualifying build, so call DeepInfra (deepseek-ai/DeepSeek-V3.2) or SambaNova (DeepSeek-V3.2) instead
3. Outside vLLM, build prompts with encoding/encoding_dsv32.py and wrap parse_message_from_completion_text in error handling, since DeepSeek says it handles well-formed output only
4. Pick thinking or chat with thinking_mode, and read the reasoning from reasoning_content
5. Send developer messages only for search-agent prompts, the only use DeepSeek gives that role
6. Use temperature 1.0 and top_p 0.95 and keep prompts within 128K tokens

### 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

## Questions

### Which is better for AI agents, DeepSeek-V3.2 or Nemotron 3 Nano Omni 30B A3B Reasoning?

Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 4 of 5 scored categories. DeepSeek-V3.2 leads on capability.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "deepseek-v3-2", "b": "nemotron-3-nano-omni-30b-a3b-reasoning"}`. From a terminal: `anchor compare deepseek-v3-2 nemotron-3-nano-omni-30b-a3b-reasoning`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json

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