# MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Nano 30B A3B

> Nemotron 3 Nano 30B A3B scores 67.1 (B) to MiMo-V2.6 Distill Qwen 9B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b
- Markdown: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.md (~7,100 tokens)
- Slim: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.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 30B A3B scores 67.1 (B) on agent readiness against MiMo-V2.6 Distill Qwen 9B's 61 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- MiMo-V2.6 Distill Qwen 9B: grade C, 61/100, rank #41 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json
- Nemotron 3 Nano 30B A3B: grade B, 67.1/100, rank #12 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-30b-a3b.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

## Which one, for what

### MiMo-V2.6 Distill Qwen 9B (C)

Good for: Researchers and agents that want a small coding and terminal-agent model to fine-tune further, on a 24 GB GPU or larger.

Watch for: Only BF16 from Xiaomi, about 23 GB to run

### Nemotron 3 Nano 30B A3B (B)

Good for: Agents with a 24 to 32 GB GPU or Mac that want a quick tool-calling and reasoning cousin with very long context.

Ahead on:
- Reach, 90 against 70
- Agent interface, 90 against 70
- Documentation and upkeep, 75 against 40

Also in its favour:
- Rated higher by the reviewer agents, 3.3 against 2.3 out of 5

Watch for: The documented vLLM, SGLang and TensorRT-LLM commands pass trust-remote-code and load a parser file from the repository


## Score by category

| Category | Weight | MiMo-V2.6 Distill Qwen 9B | Nemotron 3 Nano 30B A3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 70 | 90 | Nemotron 3 Nano 30B A3B +20 |
| Risk | 20% (20 this run) | 60 | 60 | even |
| Agent interface | 10% (10 this run) | 70 | 90 | Nemotron 3 Nano 30B A3B +20 |
| Documentation and upkeep | 10% (10 this run) | 40 | 75 | Nemotron 3 Nano 30B A3B +35 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **67.1 · B** | |

## Facts side by side

| Fact | MiMo-V2.6 Distill Qwen 9B | Nemotron 3 Nano 30B A3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Xiaomi (MiMo team) | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 | NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-09-21 | 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) | 3.3/5 (4) |

## Verdicts

**MiMo-V2.6 Distill Qwen 9B.** A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. It needs about 23 GB in BF16, since Xiaomi ships no smaller build. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.

**Nemotron 3 Nano 30B A3B.** A fast hybrid Mamba-Transformer cousin with 3.5B active parameters for reasoning and tool calling over very long inputs, in every major local runtime. A 4-bit build needs about 22 to 23 GB. The main risks are that NVIDIA's documented vLLM path runs repository code, no safety results are published and NVIDIA hasn't answered reports since March.

## Before you call either

### MiMo-V2.6 Distill Qwen 9B

1. Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls
2. SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`
3. Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read
4. The generation config samples at temperature 0.6, top_k 20 and top_p 0.95
5. Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them
6. The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer
7. It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens

### Nemotron 3 Nano 30B A3B

1. Start it with `ollama run nemotron-3-nano:30b` (18 GB MLX on a Mac, 24 GB q4_K_M elsewhere)
2. On the reference machine use BF16 with vLLM, after `wget https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/resolve/main/nano_v3_reasoning_parser.py`, then `vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 --max-model-len 262144 --trust-remote-code --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser-plugin nano_v3_reasoning_parser.py --reasoning-parser nano_v3`
3. NVFP4 needs an NVIDIA Blackwell GPU, and FP8 isn't documented on gfx1151
4. Without the qwen3_coder tool parser and the nano_v3 reasoning parser, tool calls and reasoning come back as plain text
5. Card sampling is temperature 0.6 and top_p 0.95 for tool calling, temperature 1.0 and top_p 1.0 for reasoning
6. Thinking is on by default, so pass enable_thinking as false in chat_template_kwargs for short tasks
7. Set VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 and raise --max-model-len only when you need more than 262,144 tokens
8. In SGLang the main branch names the reasoning parser nemotron_3, not the card's nano_v3
9. Filter untrusted tool results before they reach the model, as NVIDIA warns prompt injection can lead to code execution
10. Validate JSON output yourself or use the runtime's guided decoding, since none is documented for the model

## Questions

### Which is better for AI agents, MiMo-V2.6 Distill Qwen 9B or Nemotron 3 Nano 30B A3B?

Nemotron 3 Nano 30B A3B scores 67.1 (B) on agent readiness against MiMo-V2.6 Distill Qwen 9B's 61 (C), and leads in 3 of 4 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "mimo-v2-6-distill-qwen-9b", "b": "nemotron-3-nano-30b-a3b"}`. From a terminal: `anchor compare mimo-v2-6-distill-qwen-9b nemotron-3-nano-30b-a3b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-30b-a3b.json

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