# MiniMax-M2.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning

> Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) to MiniMax-M2.5's 57.5 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning
- Markdown: https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md (~7,650 tokens)
- Slim: https://www.anchorterminal.com/compare/minimax-m2-5-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/minimax-m2-5-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 MiniMax-M2.5's 57.5 (C), and leads in 4 of 5 scored categories. MiniMax-M2.5 leads on capability. Both do open-weight models you run yourself.

- MiniMax-M2.5: grade C, 57.5/100, rank #71 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.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

### MiniMax-M2.5 (C)

Good for: Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy

Ahead on:
- Capability, 73 against 34

Watch for: 230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine

### 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 65
- Risk, 60 against 30
- Agent interface, 90 against 75
- Documentation and upkeep, 65 against 22

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 1.8 out of 5

Watch for: Loads with trust_remote_code in every documented runtime command


## Score by category

| Category | Weight | MiniMax-M2.5 | Nemotron 3 Nano Omni 30B A3B Reasoning | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 73 | 34 | MiniMax-M2.5 +39 |
| Reach | 25% (25 this run) | 65 | 85 | Nemotron 3 Nano Omni 30B A3B Reasoning +20 |
| Risk | 20% (20 this run) | 30 | 60 | Nemotron 3 Nano Omni 30B A3B Reasoning +30 |
| Agent interface | 10% (10 this run) | 75 | 90 | Nemotron 3 Nano Omni 30B A3B Reasoning +15 |
| Documentation and upkeep | 10% (10 this run) | 22 | 65 | Nemotron 3 Nano Omni 30B A3B Reasoning +43 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **57.5 · C** | **60.7 · C** | |

## Facts side by side

| Fact | MiniMax-M2.5 | Nemotron 3 Nano Omni 30B A3B Reasoning |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | MiniMax | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MiniMax Model License (model) and modified MIT (code) | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-02-12 | 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 | 1.8/5 (4) | 3/5 (4) |

## Verdicts

**MiniMax-M2.5.** MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.

**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

### MiniMax-M2.5

1. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think
2. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code
3. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache
4. On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory
5. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends
6. Budget output tokens for thinking on every turn, since the template always opens a think block
7. Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy
8. Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026

### 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, MiniMax-M2.5 or Nemotron 3 Nano Omni 30B A3B Reasoning?

Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 4 of 5 scored categories. MiniMax-M2.5 leads on capability.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minimax-m2-5", "b": "nemotron-3-nano-omni-30b-a3b-reasoning"}`. From a terminal: `anchor compare minimax-m2-5 nemotron-3-nano-omni-30b-a3b-reasoning`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json

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