# Arete-27B vs Qwen3-4B-Instruct-2507 (slim)

> Arete-27B and Qwen3-4B-Instruct-2507 score within a point of each other for open-weight models you run yourself, 55.1 and 54.5 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-4b-instruct-2507.md (~9,150 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-4b-instruct-2507.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-4b-instruct-2507
- 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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Arete-27B and Qwen3-4B-Instruct-2507 score within a point of each other on agent readiness, 55.1 (C) and 54.5 (C). Qwen3-4B-Instruct-2507 leads on reach and agent interface. 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
- Qwen3-4B-Instruct-2507: C 54.5, rank #130 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.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 26.
- Qwen3-4B-Instruct-2507, good for Agents that want a small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context. Ahead on Reach, 90 against 50; Agent interface, 75 against 60.

| Category | Arete-27B | Qwen3-4B-Instruct-2507 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 90 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 60 | 75 |
| Documentation and upkeep (10%) | 63 | 26 |

| Fact (where they differ) | Arete-27B | Qwen3-4B-Instruct-2507 |
| --- | --- | --- |
| Vendor | Nous Research | Alibaba (Qwen team) |
| Last release | 2026-11-06 | 2025-09-17 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Reach, Qwen3-4B-Instruct-2507 +40: 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.); Qwen3-4B-Instruct-2507 90 (Memory 30, LM Studio's and Ollama's 4-bit builds are 2.3 to 2.5 GB, about 3 GB with a fifth added, inside 16 GB.)
- Documentation and upkeep, Arete-27B +37: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); Qwen3-4B-Instruct-2507 26 (Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, named languages and a knowledge cut-off aren't.)
- Agent interface, Qwen3-4B-Instruct-2507 +15: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); Qwen3-4B-Instruct-2507 75 (Chat template 20, a Jinja template in tokenizer_config.json.)