# LFM3-Omni-2B vs Nanbeige4.2-3B (slim)

> LFM3-Omni-2B and Nanbeige4.2-3B 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-nanbeige-4-2-3b.md (~9,800 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-nanbeige-4-2-3b.json · canonical https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-nanbeige-4-2-3b
- 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 Nanbeige4.2-3B score within a point of each other on agent readiness, 61 (C) and 61 (C). Nanbeige4.2-3B leads on reach, risk, 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
- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.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
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU Ahead on Reach, 85 against 80; Risk, 55 against 40; Agent interface, 85 against 70; Documentation and upkeep, 72 against 49.

| Category | LFM3-Omni-2B | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 85 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 49 | 72 |

| Fact (where they differ) | LFM3-Omni-2B | Nanbeige4.2-3B |
| --- | --- | --- |
| Vendor | Liquid AI | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-09-11 |

Why the edge:
- Documentation and upkeep, Nanbeige4.2-3B +23: 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)…); Nanbeige4.2-3B 72 (Model card 17, Intended use, limitations, the architecture, the parameters (3B outside the embeddings), the context and the languages (in the metadata) are on t…)
- Risk, Nanbeige4.2-3B +15: LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Agent interface, Nanbeige4.2-3B +15: 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.); Nanbeige4.2-3B 85 (Chat template 20, A Jinja chat template in tokenizer_config.json (7,961 characters), with enable_thinking, preserve_thinking, tools and tool_call_format switche…)
- Reach, Nanbeige4.2-3B +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.); Nanbeige4.2-3B 85 (Memory 30, the smallest build from Nanbeige is the FP8 repository (the 8-bit GPTQ one is the same size), 5.19 GB, and 5.19 GB × 1.2 = 6.2 GB, within 16 GB.)