# Agents-A1-4B vs LFM3-Omni-2B (slim)

> Agents-A1-4B and LFM3-Omni-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/agents-a1-4b-vs-lfm3-omni-2b.md (~8,950 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-omni-2b.json · canonical https://www.anchorterminal.com/compare/agents-a1-4b-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)

Agents-A1-4B and LFM3-Omni-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Omni-2B leads on documentation and upkeep. Both do open-weight models you run yourself.

- Agents-A1-4B: C 61, rank #39 of 160 open-weight models · https://www.anchorterminal.com/tools/agents-a1-4b.min.md
- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md
- Agents-A1-4B, good for Local agent loops (search, research, tool calls) on a laptop, a small GPU or a phone-class machine, under a plain licence Ahead on Reach, 90 against 80; Risk, 55 against 40.
- 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 Documentation and upkeep, 49 against 43.

| Category | Agents-A1-4B | LFM3-Omni-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 80 |
| Risk (20%) | 55 | 40 |
| Agent interface (10%) | 70 | 70 |
| Documentation and upkeep (10%) | 43 | 49 |

| Fact (where they differ) | Agents-A1-4B | LFM3-Omni-2B |
| --- | --- | --- |
| Vendor | InternScience (Shanghai AI Laboratory) | Liquid AI |
| Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-07-14 | 2026-11-03 |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Risk, Agents-A1-4B +15: Agents-A1-4B 55 (File safety 25, safetensors and GGUF only and nothing from the repository runs.); LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Reach, Agents-A1-4B +10: Agents-A1-4B 90 (Memory 30, InternScience's Q4_K_M GGUF with its vision projector is 3.4 GB and needs about 4.1 GB with the fifth added.); 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.)
- Documentation and upkeep, LFM3-Omni-2B +6: Agents-A1-4B 43 (Model card 8, it covers intended use, parameters and context but not the architecture, limitations, languages or a knowledge 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)…)