# gpt-oss-20b vs LFM3-Omni-2B (slim)

> gpt-oss-20b scores 69.9 (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.

- Full: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-omni-2b.md (~9,550 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-omni-2b.json · canonical https://www.anchorterminal.com/compare/gpt-oss-20b-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)

gpt-oss-20b scores 69.9 (B) on agent readiness against LFM3-Omni-2B's 61 (C), and leads in 3 of 4 scored categories. LFM3-Omni-2B leads on documentation and upkeep. Both do open-weight models you run yourself.

- gpt-oss-20b: B 69.9, rank #8 of 160 open-weight models · https://www.anchorterminal.com/tools/gpt-oss-20b.min.md
- LFM3-Omni-2B: C 61, rank #71 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-omni-2b.min.md
- gpt-oss-20b, good for Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time Ahead on Reach, 90 against 80; Risk, 85 against 40; Agent interface, 90 against 70.
- 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 42.

| Category | gpt-oss-20b | LFM3-Omni-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 80 |
| Risk (20%) | 85 | 40 |
| Agent interface (10%) | 90 | 70 |
| Documentation and upkeep (10%) | 42 | 49 |

| Fact (where they differ) | gpt-oss-20b | LFM3-Omni-2B |
| --- | --- | --- |
| Vendor | OpenAI | Liquid AI |
| Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2025-08-26 | 2026-11-03 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Risk, gpt-oss-20b +45: gpt-oss-20b 85 (File safety earns 25, since the weights are safetensors and metal/model.bin is OpenAI's own raw Metal format rather than pickle, and nothing in the repository r…); LFM3-Omni-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Agent interface, gpt-oss-20b +20: gpt-oss-20b 90 (The chat template earns 20, a Jinja file in the repository.); 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.)
- Reach, gpt-oss-20b +10: gpt-oss-20b 90 (Memory earns 25, since OpenAI's own MXFP4 build is 13.76 GB and a fifth on top is 16.5 GB, just past the 16 GB band, and Ollama's 14 GB build lands in the same…); 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 +7: gpt-oss-20b 42 (The model card earns 17, covering six of the seven points and missing a statement of supported languages.); 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)…)