# gpt-oss-120b vs LFM3-VL-2B (slim)

> gpt-oss-120b scores 70.2 (BB) to LFM3-VL-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-120b-vs-lfm3-vl-2b.md (~8,950 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-vl-2b.json · canonical https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-vl-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-120b scores 70.2 (BB) on agent readiness against LFM3-VL-2B's 61 (C), and leads in 1 of 4 scored categories. LFM3-VL-2B leads on reach and documentation and upkeep. Both do open-weight models you run yourself.

- gpt-oss-120b: BB 70.2, rank #6 of 160 open-weight models · https://www.anchorterminal.com/tools/gpt-oss-120b.min.md
- LFM3-VL-2B: C 61, rank #72 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-vl-2b.min.md
- gpt-oss-120b, good for Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support Ahead on Risk, 95 against 40. Also Agent-ready, a grade of BB or better.
- LFM3-VL-2B, good for Agents on a laptop, phone or robot that need to read screens, documents, images and video from a model under 2 GB at 4 bits Ahead on Reach, 85 against 75; Documentation and upkeep, 77 against 45.

| Category | gpt-oss-120b | LFM3-VL-2B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 85 |
| Risk (20%) | 95 | 40 |
| Agent interface (10%) | 90 | 90 |
| Documentation and upkeep (10%) | 45 | 77 |

| Fact (where they differ) | gpt-oss-120b | LFM3-VL-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 | 2026-11-09 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Risk, gpt-oss-120b +55: gpt-oss-120b 95 (File safety earns 25, safetensors only, with metal/model.bin a raw format and not pickle, and nothing from the repository runs on load.); LFM3-VL-2B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Documentation and upkeep, LFM3-VL-2B +32: gpt-oss-120b 45 (The model card earns 20, with all seven items in OpenAI's arXiv card.); LFM3-VL-2B 77 (Model card 17, Intended use (questions about video, documents, charts and app screens, finding objects, spatial reasoning), a limitation (not recommended for co…)
- Reach, LFM3-VL-2B +10: gpt-oss-120b 75 (Memory earns 10, because the smallest 4-bit build, Ollama's 65 GB gpt-oss:120b, needs about 78 GB with the fifth added, which fits the reference machine but not…); LFM3-VL-2B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.20 GB projector file, and 1.30 GB × 1.2 = 1.6 GB, which fits 8 GB, well inside the 16 GB line.)