# Arete-27B vs GLM-4.7-Flash (slim)

> GLM-4.7-Flash scores 63 (B) to Arete-27B's 55.1 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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GLM-4.7-Flash scores 63 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in 2 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
- GLM-4.7-Flash: B 63, rank #26 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-7-flash.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 28.
- GLM-4.7-Flash, good for Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime Ahead on Reach, 80 against 50; Agent interface, 85 against 60.

| Category | Arete-27B | GLM-4.7-Flash |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 63 | 28 |

| Fact (where they differ) | Arete-27B | GLM-4.7-Flash |
| --- | --- | --- |
| Vendor | Nous Research | Z.ai (Zhipu AI) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-11-06 | 2026-01-29 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Documentation and upkeep, Arete-27B +35: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); GLM-4.7-Flash 28 (The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 0, as the card describes none.)
- Reach, GLM-4.7-Flash +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.); GLM-4.7-Flash 80 (Memory earns 25, since Ollama's smallest build is the 19 GB q4_K_M one, about 22.8 GB with the fifth added, which fits 24 GB.)
- Agent interface, GLM-4.7-Flash +25: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); GLM-4.7-Flash 85 (A Jinja chat template sits in the repository, for 20. The tool-calling format is the full 25, because Z.ai itself names the glm47 parser for vLLM and SGLang, sa…)