# gpt-oss-20b vs Ornith-1.5-122B (slim)

> gpt-oss-20b scores 69.9 (B) to Ornith-1.5-122B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- 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
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gpt-oss-20b scores 69.9 (B) on agent readiness against Ornith-1.5-122B's 61 (C), and leads in every scored category. 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
- Ornith-1.5-122B: C 61, rank #81 of 160 open-weight models · https://www.anchorterminal.com/tools/ornith-1-5-122b.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 75; Risk, 85 against 50; Agent interface, 90 against 85; Documentation and upkeep, 42 against 36.
- Ornith-1.5-122B, good for Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required

| Category | gpt-oss-20b | Ornith-1.5-122B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 75 |
| Risk (20%) | 85 | 50 |
| Agent interface (10%) | 90 | 85 |
| Documentation and upkeep (10%) | 42 | 36 |

| Fact (where they differ) | gpt-oss-20b | Ornith-1.5-122B |
| --- | --- | --- |
| Vendor | OpenAI | Ornith |
| Licence | Apache-2.0 | MIT |
| Last release | 2025-08-26 | 2026-10-24 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Risk, gpt-oss-20b +35: 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…); Ornith-1.5-122B 50 (File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories for this size, so the card's --trust-remote-code flag loads nothing from…)
- Reach, gpt-oss-20b +15: 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…); Ornith-1.5-122B 75 (Memory 10, since Ornith's own MLX 4-bit build is 69.7 GB and needs about 83.6 GB with the fifth added, over 64 GB and inside the reference machine's 107.4 GB, a…)
- Documentation and upkeep, gpt-oss-20b +6: gpt-oss-20b 42 (The model card earns 17, covering six of the seven points and missing a statement of supported languages.); Ornith-1.5-122B 36 (Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.)
- Agent interface, gpt-oss-20b +5: gpt-oss-20b 90 (The chat template earns 20, a Jinja file in the repository.); Ornith-1.5-122B 85 (Chat template 20, a Jinja file in the repository.)