# MiMo-V2.6 Distill Qwen 9B vs OTel-2.0-LLM-31B-IT (slim)

> MiMo-V2.6 Distill Qwen 9B scores 61 (C) to OTel-2.0-LLM-31B-IT's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against OTel-2.0-LLM-31B-IT's 56.8 (C), and leads in 3 of 4 scored categories. OTel-2.0-LLM-31B-IT leads on documentation and upkeep. Both do open-weight models you run yourself.

- MiMo-V2.6 Distill Qwen 9B: C 61, rank #47 of 160 open-weight models · https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.min.md
- OTel-2.0-LLM-31B-IT: C 56.8, rank #111 of 160 open-weight models · https://www.anchorterminal.com/tools/otel-2-0-llm-31b-it.min.md
- MiMo-V2.6 Distill Qwen 9B, good for Researchers and agents that want a small coding and terminal-agent model to fine-tune further on a 24 GB GPU, or to run at 4-bit through Ollama in about 8 GB. Ahead on Reach, 80 against 50; Risk, 65 against 55; Agent interface, 70 against 60.
- OTel-2.0-LLM-31B-IT, good for Telecoms teams that want an open model for standards questions and RAG on their own hardware Ahead on Documentation and upkeep, 74 against 40.

| Category | MiMo-V2.6 Distill Qwen 9B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 50 |
| Risk (20%) | 65 | 55 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 40 | 74 |

| Fact (where they differ) | MiMo-V2.6 Distill Qwen 9B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Xiaomi (MiMo team) | AT&T (Open Telco AI) |
| Licence | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 | Apache-2.0 |
| Last release | 2026-09-21 | 2026-11-01 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +34: MiMo-V2.6 Distill Qwen 9B 40 (Model card 5 of 20, intended use and parameters only.); OTel-2.0-LLM-31B-IT 74 (Model card 14, Intended use, a long limitations section, the architecture and training method, the parameters (31B) and the language (English) are on the card.)
- Reach, MiMo-V2.6 Distill Qwen 9B +30: MiMo-V2.6 Distill Qwen 9B 80 (Memory 30 of 30, Ollama's library build at q4_K_M is 6.6 GB, 7.9 GB with a fifth added, while Xiaomi's only build is BF16 at 18.85 GB.); OTel-2.0-LLM-31B-IT 50 (Memory 10, the publisher's only build is the BF16 safetensors, 62.55 GB for the 15 shards the index names, and 62.55 GB × 1.2 = 75.1 GB, above 64 GB and inside…)
- Risk, MiMo-V2.6 Distill Qwen 9B +10: MiMo-V2.6 Distill Qwen 9B 65 (File safety 25, safetensors only and no repository code runs.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)
- Agent interface, MiMo-V2.6 Distill Qwen 9B +10: MiMo-V2.6 Distill Qwen 9B 70 (Chat template 20, a Jinja file in the repository.); OTel-2.0-LLM-31B-IT 60 (Chat template 20, chat_template.jinja in the repository, 19,300 characters, the publisher's own.)