# LFM3-Omni-2B vs LFM3-VL-2B (slim)

> LFM3-Omni-2B and LFM3-VL-2B 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-lfm3-vl-2b.md (~9,250 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-lfm3-vl-2b.json · canonical https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-lfm3-vl-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 and LFM3-VL-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-VL-2B leads on reach, agent interface 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
- LFM3-VL-2B: C 61, rank #72 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-vl-2b.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
- LFM3-VL-2B, good for Agents on a laptop, phone or robot that need to read screens, documents, images and video from a model under 2 GB at 4 bits Ahead on Reach, 85 against 80; Agent interface, 90 against 70; Documentation and upkeep, 77 against 49.

| Category | LFM3-Omni-2B | LFM3-VL-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 85 |
| Risk (20%) | 40 | 40 |
| Agent interface (10%) | 70 | 90 |
| Documentation and upkeep (10%) | 49 | 77 |

| Fact (where they differ) | LFM3-Omni-2B | LFM3-VL-2B |
| --- | --- | --- |
| Last release | 2026-11-03 | 2026-11-09 |

Why the edge:
- Documentation and upkeep, LFM3-VL-2B +28: 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)…); LFM3-VL-2B 77 (Model card 17, Intended use (questions about video, documents, charts and app screens, finding objects, spatial reasoning), a limitation (not recommended for co…)
- Agent interface, LFM3-VL-2B +20: 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.); LFM3-VL-2B 90 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, images and video, tools, deferred tools, tool results and the thinking…)
- Reach, LFM3-VL-2B +5: 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.); LFM3-VL-2B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.20 GB projector file, and 1.30 GB × 1.2 = 1.6 GB, which fits 8 GB, well inside the 16 GB line.)