# Devstral Small 2 vs Qwen3.5-122B-A10B (slim)

> Qwen3.5-122B-A10B scores 63.1 (B) to Devstral Small 2's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-122b-a10b.md (~9,900 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-122b-a10b.json · canonical https://www.anchorterminal.com/compare/devstral-small-2-vs-qwen3-5-122b-a10b
- 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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Qwen3.5-122B-A10B scores 63.1 (B) on agent readiness against Devstral Small 2's 61 (C), and leads in 1 of 4 scored categories. Devstral Small 2 leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- Devstral Small 2: C 61, rank #60 of 160 open-weight models · https://www.anchorterminal.com/tools/devstral-small-2.min.md
- Qwen3.5-122B-A10B: B 63.1, rank #25 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-122b-a10b.min.md
- Devstral Small 2, good for Developers who want a dependable local coding agent on one consumer GPU or a 32 GB Mac Ahead on Reach, 90 against 80; Risk, 60 against 55; Documentation and upkeep, 46 against 34.
- Qwen3.5-122B-A10B, good for Agents with a 128 GB unified-memory machine or two large GPUs that want a capable vision-language model with a plain licence. Ahead on Agent interface, 70 against 65.

| Category | Devstral Small 2 | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 80 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 65 | 70 |
| Documentation and upkeep (10%) | 46 | 34 |

| Fact (where they differ) | Devstral Small 2 | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Vendor | Mistral AI | Alibaba (Qwen team) |
| Last release | 2026-07-15 | 2026-02-24 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, Devstral Small 2 +12: Devstral Small 2 46 (Model card 11, Intended use, the architecture, the parameters and the context are on the card.); Qwen3.5-122B-A10B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).)
- Reach, Devstral Small 2 +10: Devstral Small 2 90 (Memory 25, the smallest build at 4 bits from a runtime's own library is Ollama's devstral-small-2 at Q4_K_M, 15 GB, and 15 GB × 1.2 = 18 GB, within 24 GB.); Qwen3.5-122B-A10B 80 (Memory earns 10 of 30, since Alibaba's GPTQ 4-bit build is 78.9 GB, about 95 GB with a fifth added, which fits our reference machine but no smaller band.)
- Risk, Devstral Small 2 +5: Devstral Small 2 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); Qwen3.5-122B-A10B 55 (Safetensors only with no repository code run on load or to build prompts gives file safety 25, and files in the Qwen organisation the publisher's GitHub links t…)
- Agent interface, Qwen3.5-122B-A10B +5: Devstral Small 2 65 (Chat template 20, chat_template.jinja in the repository (11,362 characters), with the tokenizer's tekken file for mistral-common.); Qwen3.5-122B-A10B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20).)