# Arete-27B vs LBS-27B (slim)

> LBS-27B and Arete-27B score within a point of each other for open-weight models you run yourself, 55.8 and 55.1 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/arete-27b-vs-lbs-27b.md (~8,500 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-lbs-27b.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-lbs-27b
- 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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LBS-27B and Arete-27B score within a point of each other on agent readiness, 55.8 (C) and 55.1 (C). 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
- LBS-27B: C 55.8, rank #118 of 160 open-weight models · https://www.anchorterminal.com/tools/lbs-27b.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 43.
- LBS-27B, good for Agents with about 96 GB of GPU memory that need to find click targets on dense professional screenshots, or read fine detail in large images, and can run a small crop loop and wait for independent results. Ahead on Reach, 60 against 50; Agent interface, 70 against 60.

| Category | Arete-27B | LBS-27B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 60 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 63 | 43 |

| Fact (where they differ) | Arete-27B | LBS-27B |
| --- | --- | --- |
| Vendor | Nous Research | inclusionAI (Ant Group) |
| Licence | Apache-2.0 | Apache-2.0 (the card's metadata and licence section; the LICENSE file sits in the GitHub repository inclusionAI/UI-Venus on its LBS branch, not in the Hugging Face repository) |
| Last release | 2026-11-06 | 2026-10-26 |

Why the edge:
- Documentation and upkeep, Arete-27B +20: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); LBS-27B 43 (The model card earns 8, with intended use, one limitation and parameters, and no architecture, context, languages or cut-off.)
- Reach, LBS-27B +10: 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.); LBS-27B 60 (Memory earns 10, since the only build is 54.73 GB of BF16, about 66 GB with a fifth added, which fits the reference machine but not 64 GB.)
- Agent interface, LBS-27B +10: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); LBS-27B 70 (The chat template earns 20, Qwen's Jinja file in the repository.)
- Risk, Arete-27B +5: Arete-27B 55 (File safety 25, safetensors only and no remote code.); LBS-27B 50 (File safety earns 15, safetensors only but with the documented route running the publisher's scripts to serve it and to write its system prompt.)