# Arete-27B vs Qwen3-VL-32B-Instruct (slim)

> Qwen3-VL-32B-Instruct scores 56.4 (C) to Arete-27B's 55.1 (C) 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-vl-32b-instruct.md (~8,850 tokens) · this version ~580 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-vl-32b-instruct.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-qwen3-vl-32b-instruct
- 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)

Qwen3-VL-32B-Instruct scores 56.4 (C) on agent readiness against Arete-27B's 55.1 (C), and leads in 1 of 4 scored categories. Arete-27B leads on documentation and upkeep. 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-VL-32B-Instruct: C 56.4, rank #115 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct.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 31.
- Qwen3-VL-32B-Instruct, good for An agent with a 32 GB GPU or more that wants the largest dense Qwen3-VL model for images, documents and video Ahead on Reach, 85 against 50.

| Category | Arete-27B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 85 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 63 | 31 |

| Fact (where they differ) | Arete-27B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Vendor | Nous Research | Alibaba (Qwen team) |
| Last release | 2026-11-06 | 2025-11-01 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Reach, Qwen3-VL-32B-Instruct +35: 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-VL-32B-Instruct 85 (Alibaba's own Q4_K_M GGUF is 19.76 GB and 20.53 GB with the vision file it needs for images, so with a fifth added it needs about 25 GB and the 32 GB band (20).)
- Documentation and upkeep, Arete-27B +32: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); Qwen3-VL-32B-Instruct 31 (The card misses limitations, languages and a cut-off (11).)