# Arete-27B vs LFM3-Omni-2B (slim)

> LFM3-Omni-2B scores 61 (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-lfm3-omni-2b.md (~8,900 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-omni-2b.json · canonical https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-omni-2b
- 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)

LFM3-Omni-2B scores 61 (C) 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
- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.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 40; Documentation and upkeep, 63 against 49.
- LFM3-Omni-2B, good for Voice and camera agents on a laptop or phone that want one small model for hearing, seeing, speaking and calling tools Ahead on Reach, 80 against 50; Agent interface, 70 against 60.

| Category | Arete-27B | LFM3-Omni-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 80 |
| Risk (20%) | 55 | 40 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 63 | 49 |

| Fact (where they differ) | Arete-27B | LFM3-Omni-2B |
| --- | --- | --- |
| Vendor | Nous Research | Liquid AI |
| Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-11-06 | 2026-11-03 |

Why the edge:
- Reach, LFM3-Omni-2B +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.); LFM3-Omni-2B 80 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.29 GB projector file, and 1.39 GB × 1.2 = 1.7 GB, which fits 8 GB, well inside the 16 GB line.)
- Risk, Arete-27B +15: Arete-27B 55 (File safety 25, safetensors only and no remote code.); LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Documentation and upkeep, Arete-27B +14: Arete-27B 63 (Model card 8, no limitations, context length, languages or cut-off.); LFM3-Omni-2B 49 (Model card 14, Intended use (one on-device model in place of separate speech recognition, vision, language and speech models), architecture, parameters (2.17B)…)
- Agent interface, LFM3-Omni-2B +10: Arete-27B 60 (Chat template 20, a Jinja file in the repository.); LFM3-Omni-2B 70 (Chat template 20, chat_template.jinja in the repository (13,513 characters), with roles, images, video and audio, tools, deferred tools and tool results.)