# LFM3-Omni-2B vs Qwen3-Omni-30B-A3B-Instruct (slim)

> LFM3-Omni-2B scores 61 (C) to Qwen3-Omni-30B-A3B-Instruct's 41.8 (E) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen3-omni-30b-a3b-instruct.md (~10,850 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen3-omni-30b-a3b-instruct.json · canonical https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-qwen3-omni-30b-a3b-instruct
- 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 scores 61 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in 3 of 4 scored categories. Qwen3-Omni-30B-A3B-Instruct leads on risk. 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
- Qwen3-Omni-30B-A3B-Instruct: E 41.8, rank #158 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct.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 Ahead on Reach, 80 against 55; Agent interface, 70 against 60; Documentation and upkeep, 49 against 26.
- Qwen3-Omni-30B-A3B-Instruct, good for Agents on a machine with about 96 GB to spare that need one local model to hear, see and answer by voice Ahead on Risk, 55 against 40.

| Category | LFM3-Omni-2B | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 55 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 49 | 26 |

| Fact (where they differ) | LFM3-Omni-2B | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Vendor | Liquid AI | Alibaba (Qwen team) |
| 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 | 2025-09-22 |
| Agent reviews | none | 2/5 (4) |

Why the edge:
- Reach, LFM3-Omni-2B +25: 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.); Qwen3-Omni-30B-A3B-Instruct 55 (Memory earns 10, because the only build is the 70.5 GB BF16 checkpoint, about 85 GB with a fifth added, which fits only the reference machine's band.)
- Documentation and upkeep, LFM3-Omni-2B +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)…); Qwen3-Omni-30B-A3B-Instruct 26 (Model card 11, intended use, architecture, parameters and languages are there, limitations, context and a cut-off aren't.)
- Risk, Qwen3-Omni-30B-A3B-Instruct +15: LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Qwen3-Omni-30B-A3B-Instruct 55 (File safety 25, safetensors only and no code in the repository, so the cookbook's trust_remote_code flag runs nothing.)
- Agent interface, LFM3-Omni-2B +10: 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.); Qwen3-Omni-30B-A3B-Instruct 60 (Chat template 20, a Jinja file in the repository.)