# Arete-27B vs GLM-5.3 (slim)

> GLM-5.3 scores 64.6 (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-5.3 scores 64.6 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in 2 of 4 scored categories. Arete-27B leads on risk and 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-5.3: B 64.6, rank #21 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-5-3.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 Risk, 55 against 50; Documentation and upkeep, 63 against 58.
- GLM-5.3, good for Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider Ahead on Reach, 55 against 50; Agent interface, 70 against 60.

| Category | Arete-27B | GLM-5.3 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 55 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 63 | 58 |

| Fact (where they differ) | Arete-27B | GLM-5.3 |
| --- | --- | --- |
| Vendor | Nous Research | Z.ai (Zhipu AI) |
| Licence | Apache-2.0 | GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators) |
| Last release | 2026-11-06 | 2026-10-15 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Agent interface, GLM-5.3 +10: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); GLM-5.3 70 (A Jinja chat template sits in the repository, for 20. The tool-calling format is 10, since it is defined only by the template and the glm47 parser is named by v…)
- Reach, GLM-5.3 +5: 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-5.3 55 (Memory earns nothing, since Z.ai's smallest build is the 755.6 GB FP8 one, about 907 GB with the fifth added, and Ollama only lists a cloud entry.)
- Risk, Arete-27B +5: Arete-27B 55 (File safety 25, safetensors only and no remote code.); GLM-5.3 50 (File safety is full, with safetensors only, no Python in the repository and no remote code needed in Transformers 5.12.0 or later.)
- Documentation and upkeep, Arete-27B +5: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); GLM-5.3 58 (The card covers intended use, languages and context and misses limitations, architecture, parameters and cut-off, for 8. Training data is 5, a description of th…)