# Arete-27B vs Hy3 (slim)

> Hy3 scores 62.6 (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.

- Full: https://www.anchorterminal.com/compare/arete-27b-vs-hy3.md (~8,400 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-hy3.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-hy3
- 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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Hy3 scores 62.6 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in 3 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
- Hy3: B 62.6, rank #28 of 160 open-weight models · https://www.anchorterminal.com/tools/hy3.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 56.
- Hy3, good for Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0 Ahead on Reach, 70 against 50; Risk, 60 against 55; Agent interface, 75 against 60.

| Category | Arete-27B | Hy3 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 70 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 60 | 75 |
| Documentation and upkeep (10%) | 63 | 56 |

| Fact (where they differ) | Arete-27B | Hy3 |
| --- | --- | --- |
| Vendor | Nous Research | Tencent (Hy team) |
| Last release | 2026-11-06 | 2026-07-20 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Hy3 +20: 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.); Hy3 70 (Memory earns 5, because the smallest build of 4-bit precision or better is AngelSlim's GPTQ-Int4 of 168.5 GB, about 202 GB with the fifth added, which is within…)
- Agent interface, Hy3 +15: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); Hy3 75 (The chat template earns 20, a chat_template.jinja in the repository.)
- Documentation and upkeep, Arete-27B +7: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); Hy3 56 (The model card earns 11, covering intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.)
- Risk, Hy3 +5: Arete-27B 55 (File safety 25, safetensors only and no remote code.); Hy3 60 (File safety earns the full 25, safetensors only with no pickle files, and the documented route runs vLLM or SGLang from their own code with a Jinja template, so…)