# gpt-oss-120b vs LongCat-2.5 (slim)

> gpt-oss-120b scores 70.2 (BB) to LongCat-2.5's 50.5 (D) 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-longcat-2-5.md (~8,900 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-120b-vs-longcat-2-5.json · canonical https://www.anchorterminal.com/compare/gpt-oss-120b-vs-longcat-2-5
- 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 LongCat-2.5's 50.5 (D), and leads in 3 of 4 scored categories. 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
- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.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 Reach, 75 against 35; Risk, 95 against 60; Agent interface, 90 against 75. Also Agent-ready, a grade of BB or better.
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do

| Category | gpt-oss-120b | LongCat-2.5 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 35 |
| Risk (20%) | 95 | 60 |
| Agent interface (10%) | 90 | 75 |
| Documentation and upkeep (10%) | 45 | 46 |

| Fact (where they differ) | gpt-oss-120b | LongCat-2.5 |
| --- | --- | --- |
| Vendor | OpenAI | Meituan (LongCat) |
| Licence | Apache-2.0 | MIT |
| Last release | 2025-08-26 | 2026-11-10 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Reach, gpt-oss-120b +40: 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…); LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.)
- Risk, gpt-oss-120b +35: 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.); LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Agent interface, gpt-oss-120b +15: gpt-oss-120b 90 (The chat template earns 20, a Jinja file in the repository.); LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.)