# gpt-oss-120b vs LFM3-1.7B (slim)

> gpt-oss-120b scores 70.2 (BB) to LFM3-1.7B'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-lfm3-1-7b.md (~9,350 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b.json · canonical https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b
- 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 LFM3-1.7B's 61 (C), and leads in 1 of 4 scored categories. LFM3-1.7B leads on reach, agent interface 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
- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.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.
- LFM3-1.7B, good for Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits Ahead on Reach, 85 against 75; Agent interface, 100 against 90; Documentation and upkeep, 67 against 45.

| Category | gpt-oss-120b | LFM3-1.7B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 85 |
| Risk (20%) | 95 | 40 |
| Agent interface (10%) | 90 | 100 |
| Documentation and upkeep (10%) | 45 | 67 |

| Fact (where they differ) | gpt-oss-120b | LFM3-1.7B |
| --- | --- | --- |
| 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.); LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Documentation and upkeep, LFM3-1.7B +22: gpt-oss-120b 45 (The model card earns 20, with all seven items in OpenAI's arXiv card.); LFM3-1.7B 67 (Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-ste…)
- Reach, LFM3-1.7B +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…); LFM3-1.7B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line.)
- Agent interface, LFM3-1.7B +10: gpt-oss-120b 90 (The chat template earns 20, a Jinja file in the repository.); LFM3-1.7B 100 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch.)