# Arete-27B vs Qwen3.5-2B (slim)

> Arete-27B scores 55.1 (C) to Qwen3.5-2B's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-2b.md (~8,050 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-2b.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-5-2b
- 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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Arete-27B scores 55.1 (C) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 1 of 4 scored categories. Qwen3.5-2B leads on reach. Both do open-weight models you run yourself.

- Arete-27B: C 55.1, rank #123 of 160 open-weight models · https://www.anchorterminal.com/tools/arete-27b.min.md
- Qwen3.5-2B: D 50.5, rank #144 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-2b.min.md
- Arete-27B, good for Agents that want Qwen3.8-27B's coding and tool use without its handling of politically sensitive topics, on a 24 GB card or a 128 GB machine Ahead on Documentation and upkeep, 63 against 37.
- Qwen3.5-2B, good for Builders who want a cheap local helper or fine-tuning base for narrow tasks and image reading on a laptop, small GPU or CPU Ahead on Reach, 80 against 50.

| Category | Arete-27B | Qwen3.5-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 63 | 37 |

| Fact (where they differ) | Arete-27B | Qwen3.5-2B |
| --- | --- | --- |
| Vendor | Nous Research | Alibaba (Qwen team) |
| Last release | 2026-11-06 | 2026-03-02 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Qwen3.5-2B +30: Arete-27B 50 (Memory 10, the only build from Nous Research is the 54.7 GB BF16 release, which needs about 66 GB and fits the reference machine.); Qwen3.5-2B 80 (Memory earns the full 30, since LM Studio's Q4_K_M GGUF with its vision projector is 1.94 GB, about 2.3 GB with the fifth added (Ollama's Q4_K_M build was 1.9 G…)
- Documentation and upkeep, Arete-27B +26: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); Qwen3.5-2B 37 (The card covers six of the seven items, missing only a cut-off (17), because it states the intended uses and warns about thinking loops.)