# gpt-oss-20b vs Granite 4.2 8B (slim)

> gpt-oss-20b scores 69.9 (B) to Granite 4.2 8B'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-granite-4-2-8b.md (~9,700 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-20b-vs-granite-4-2-8b.json · canonical https://www.anchorterminal.com/compare/gpt-oss-20b-vs-granite-4-2-8b
- 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 Granite 4.2 8B's 61 (C), and leads in 2 of 4 scored categories. Granite 4.2 8B leads on reach and 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
- Granite 4.2 8B: C 61, rank #66 of 160 open-weight models · https://www.anchorterminal.com/tools/granite-4-2-8b.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 Risk, 85 against 55; Agent interface, 90 against 85.
- Granite 4.2 8B, good for Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 16 GB machine Ahead on Reach, 95 against 90; Documentation and upkeep, 92 against 42.

| Category | gpt-oss-20b | Granite 4.2 8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 95 |
| Risk (20%) | 85 | 55 |
| Agent interface (10%) | 90 | 85 |
| Documentation and upkeep (10%) | 42 | 92 |

| Fact (where they differ) | gpt-oss-20b | Granite 4.2 8B |
| --- | --- | --- |
| Vendor | OpenAI | IBM |
| Last release | 2025-08-26 | 2026-10-20 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Granite 4.2 8B +50: gpt-oss-20b 42 (The model card earns 17, covering six of the seven points and missing a statement of supported languages.); Granite 4.2 8B 92 (Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (8B), context length (128K native) and 12…)
- Risk, gpt-oss-20b +30: 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…); Granite 4.2 8B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Reach, Granite 4.2 8B +5: 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…); Granite 4.2 8B 95 (Memory 30, IBM's own 4-bit MLX build granite-4.2-8b-q4-mlx is 4.95 GB, and 4.95 GB × 1.2 = 5.9 GB, within 8 GB.)
- Agent interface, gpt-oss-20b +5: gpt-oss-20b 90 (The chat template earns 20, a Jinja file in the repository.); Granite 4.2 8B 85 (Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort.)