# MiMo-V2.6 Distill Qwen 9B vs Qwen3-Omni-30B-A3B-Instruct > MiMo-V2.6 Distill Qwen 9B scores 61 (C) to Qwen3-Omni-30B-A3B-Instruct's 41.8 (E) 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-qwen3-omni-30b-a3b-instruct - Markdown: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.md (~7,650 tokens) - Slim: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.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 Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in every scored category. 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 - Qwen3-Omni-30B-A3B-Instruct: grade E, 41.8/100, rank #99 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-omni-30b-a3b-instruct.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 conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md - All 388 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/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. Ahead on: - Reach, 70 against 55 - Risk, 60 against 55 - Agent interface, 70 against 60 - Documentation and upkeep, 40 against 26 Watch for: Only BF16 from Xiaomi, about 23 GB to run ### Qwen3-Omni-30B-A3B-Instruct (E) Good for: Agents on a machine with about 96 GB to spare that need one local model to hear, see and answer by voice Watch for: Only a 70.5 GB BF16 build, about 85 GB to run, with no quantised build from Alibaba ## Score by category | Category | Weight | MiMo-V2.6 Distill Qwen 9B | Qwen3-Omni-30B-A3B-Instruct | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 70 | 55 | MiMo-V2.6 Distill Qwen 9B +15 | | Risk | 20% (20 this run) | 60 | 55 | MiMo-V2.6 Distill Qwen 9B +5 | | Agent interface | 10% (10 this run) | 70 | 60 | MiMo-V2.6 Distill Qwen 9B +10 | | Documentation and upkeep | 10% (10 this run) | 40 | 26 | MiMo-V2.6 Distill Qwen 9B +14 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **61 · C** | **41.8 · E** | | ## Facts side by side | Fact | MiMo-V2.6 Distill Qwen 9B | Qwen3-Omni-30B-A3B-Instruct | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Xiaomi (MiMo team) | Alibaba (Qwen team) | | 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 | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-09-21 | 2025-09-22 | | 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 | 2.3/5 (4) | 2/5 (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. **Qwen3-Omni-30B-A3B-Instruct.** An omni-modal cousin that listens, watches and reads, then answers in text or one of three voices, with tool calls from spoken requests, under plain Apache 2.0. Its only build, BF16, needs about 85 GB, and speech out needs Transformers or vLLM-Omni. The main risk is no answers from Qwen and no safety work for speech-driven actions. ## 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 ### Qwen3-Omni-30B-A3B-Instruct 1. For text answers, `mkdir -p media && vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --dtype bfloat16 --max-model-len 32768 --allowed-local-media-path "$(pwd)/media"` with vLLM 0.11.1 or later serves the Thinker on an OpenAI-compatible API 2. The card's command passes `--allowed-local-media-path /`, which lets anyone who can reach the server have it read any file on the machine through a file:// URL. Point it at a dedicated folder that holds only the media you mean to send, as above, and give vLLM an absolute path 3. Send audio as `audio_url` and images as `image_url` content parts; vLLM serve doesn't take use_audio_in_video, so pass a video's audio separately 4. For speech out, load Qwen3OmniMoeForConditionalGeneration in Transformers 4.57.0 or later with qwen-omni-utils, pick speaker Ethan, Chelsie or Aiden, and write the returned waveform at 24 kHz 5. Call model.disable_talker() or pass return_audio=False when you only need text, which saves about 10 GB and time 6. Parse tool calls as JSON inside `` tags yourself, since no parser is named, and confirm actions triggered by speech before running them 7. Keep use_audio_in_video the same across every step of a conversation, the card warns results go wrong otherwise 8. Budget memory for video, the card's table rises from 78.85 GB for 15 seconds to 144.81 GB for 120 seconds in BF16 ## Questions ### Which is better for AI agents, MiMo-V2.6 Distill Qwen 9B or Qwen3-Omni-30B-A3B-Instruct? MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in every scored category. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.json, and with the fewest tokens: https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "mimo-v2-6-distill-qwen-9b", "b": "qwen3-omni-30b-a3b-instruct"}`. 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How: https://www.anchorterminal.com/agents/#mcp