# LFM3-Omni-2B vs occamy-1.0 (slim)

> LFM3-Omni-2B and occamy-1.0 score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0.md (~8,750 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0.json · canonical https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-occamy-1-0
- 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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LFM3-Omni-2B and occamy-1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). occamy-1.0 leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md
- occamy-1.0: C 61, rank #59 of 160 open-weight models · https://www.anchorterminal.com/tools/occamy-1-0.min.md
- 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
- occamy-1.0, good for Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac. Ahead on Reach, 90 against 80; Risk, 55 against 40; Documentation and upkeep, 74 against 49.

| Category | LFM3-Omni-2B | occamy-1.0 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 90 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 70 | 70 |
| Documentation and upkeep (10%) | 49 | 74 |

| Fact (where they differ) | LFM3-Omni-2B | occamy-1.0 |
| --- | --- | --- |
| Vendor | Liquid AI | Accio (Accio-Lab) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-10-02 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, occamy-1.0 +25: 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)…); occamy-1.0 74 (Model card 14 of 20, languages and a knowledge cut-off are missing.)
- Risk, occamy-1.0 +15: LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); occamy-1.0 55 (File safety 25, safetensors only and nothing from the repository runs to load it or build prompts.)
- Reach, occamy-1.0 +10: 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.); occamy-1.0 90 (Memory 25 of 30, Accio's MLX mxfp4 build is 18.4 GB, 22.1 GB with a fifth added, and its IQ4_XS GGUF needs 22.5 GB, both within 24 GB.)