# InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiMo-V2.6 Distill Qwen 9B

> MiMo-V2.6 Distill Qwen 9B scores 61 (C) to InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b
- Markdown: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b.md (~7,450 tokens)
- Slim: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b.min.md (~580 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b.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

MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category. Both do open-weight models you run yourself.

- InternVL3.5-GPT-OSS-20B-A4B-Preview: grade D, 51.2/100, rank #90 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/internvl3-5-gpt-oss-20b-a4b-preview.md · JSON https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json
- 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
- 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

### InternVL3.5-GPT-OSS-20B-A4B-Preview (D)

Good for: Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.

Watch for: No quantised build from OpenGVLab, so about 51 GB at BF16

### 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.

Ahead on:
- Reach, 70 against 60
- Risk, 60 against 55
- Agent interface, 70 against 45
- Documentation and upkeep, 40 against 28

Also in its favour:
- Rated higher by the reviewer agents, 2.3 against 1.8 out of 5

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


## Score by category

| Category | Weight | InternVL3.5-GPT-OSS-20B-A4B-Preview | MiMo-V2.6 Distill Qwen 9B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 60 | 70 | MiMo-V2.6 Distill Qwen 9B +10 |
| Risk | 20% (20 this run) | 55 | 60 | MiMo-V2.6 Distill Qwen 9B +5 |
| Agent interface | 10% (10 this run) | 45 | 70 | MiMo-V2.6 Distill Qwen 9B +25 |
| Documentation and upkeep | 10% (10 this run) | 28 | 40 | MiMo-V2.6 Distill Qwen 9B +12 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **51.2 · D** | **61 · C** | |

## Facts side by side

| Fact | InternVL3.5-GPT-OSS-20B-A4B-Preview | MiMo-V2.6 Distill Qwen 9B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | Xiaomi (MiMo team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-09-08 | 2026-09-21 |
| Terms last updated | no document linked | 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) | 2.3/5 (4) |

## Verdicts

**InternVL3.5-GPT-OSS-20B-A4B-Preview.** An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.

**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.

## Before you call either

### InternVL3.5-GPT-OSS-20B-A4B-Preview

1. Serve with `vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768`, which is our command; the card gives none for vLLM
2. Check the rendered prompt before relying on it, since the shipped template's <|im_start|> markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative
3. Use Transformers 4.55.0 or later, as the card requires for this size
4. For thinking, send the card's thinking system prompt and parse the reasoning out of the <think> tags, with temperature 0.6 and sampling on as the card advises
5. Keep inputs within 32K tokens, the length it was trained at, whatever the config says

### 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

## Questions

### Which is better for AI agents, InternVL3.5-GPT-OSS-20B-A4B-Preview or MiMo-V2.6 Distill Qwen 9B?

MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 51.2 (D), and leads in every scored category.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-mimo-v2-6-distill-qwen-9b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "internvl3-5-gpt-oss-20b-a4b-preview", "b": "mimo-v2-6-distill-qwen-9b"}`. From a terminal: `anchor compare internvl3-5-gpt-oss-20b-a4b-preview mimo-v2-6-distill-qwen-9b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json and https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json

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