# Kimi K3 vs LFM3-Omni-2B (slim)

> Kimi K3 scores 62.4 (B) to LFM3-Omni-2B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Kimi K3 scores 62.4 (B) on agent readiness against LFM3-Omni-2B's 61 (C), and leads in 1 of 4 scored categories. LFM3-Omni-2B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Kimi K3: B 62.4, rank #30 of 160 open-weight models · https://www.anchorterminal.com/tools/kimi-k3.min.md
- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md
- Kimi K3, good for Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work Ahead on Risk, 65 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 Reach, 80 against 50; Agent interface, 70 against 65; Documentation and upkeep, 49 against 41.

| Category | Kimi K3 | LFM3-Omni-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 50 | 80 |
| Risk (20%) | 65 | 40 |
| Agent interface (10%) | 65 | 70 |
| Documentation and upkeep (10%) | 41 | 49 |

| Fact (where they differ) | Kimi K3 | LFM3-Omni-2B |
| --- | --- | --- |
| Vendor | Moonshot AI | Liquid AI |
| Licence | Kimi K3 License (modified MIT) | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-09-02 | 2026-11-03 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, LFM3-Omni-2B +30: Kimi K3 50 (Memory earns nothing, because the only build of 4-bit precision or better from Moonshot or a runtime's own library is Moonshot's MXFP4 release of 1,561 GB, abou…); 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, Kimi K3 +25: Kimi K3 65 (File safety earns 15, safetensors only with no pickle files, less 10 because the documented loading path runs Moonshot's Python with trust_remote_code and build…); LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Documentation and upkeep, LFM3-Omni-2B +8: Kimi K3 41 (The model card earns 11, covering intended use, architecture, parameters and context, but not 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)…)
- Agent interface, LFM3-Omni-2B +5: Kimi K3 65 (The chat template earns 10, because there is no Jinja template and the prompt format exists only as encoding_k3.py, code you run.); 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.)