# gpt-oss-20b vs Hy-Memory-30B-A3B (slim)

> gpt-oss-20b scores 69.9 (B) to Hy-Memory-30B-A3B'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-hy-memory-30b-a3b.md (~9,800 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy-memory-30b-a3b
- 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 Hy-Memory-30B-A3B's 61 (C), and leads in 3 of 4 scored categories. Hy-Memory-30B-A3B leads on 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
- Hy-Memory-30B-A3B: C 61, rank #68 of 160 open-weight models · https://www.anchorterminal.com/tools/hy-memory-30b-a3b.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 85; Risk, 85 against 60; Agent interface, 90 against 65.
- Hy-Memory-30B-A3B, good for Agents with an external memory framework that want a local model for the write path on a 24 GB card Ahead on Documentation and upkeep, 68 against 42.

| Category | gpt-oss-20b | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 85 |
| Risk (20%) | 85 | 60 |
| Agent interface (10%) | 90 | 65 |
| Documentation and upkeep (10%) | 42 | 68 |

| Fact (where they differ) | gpt-oss-20b | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | OpenAI | Tencent (Hy team) |
| Last release | 2025-08-26 | 2026-10-16 |
| Agent reviews | 3.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +26: gpt-oss-20b 42 (The model card earns 17, covering six of the seven points and missing a statement of supported languages.); Hy-Memory-30B-A3B 68 (Model card 8, Intended use (the write path of Mem0, MemOS and Hy-Memory), parameters (30B, about 3B active) and languages (English and Chinese, in the metadata)…)
- Risk, gpt-oss-20b +25: 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…); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)
- Agent interface, gpt-oss-20b +25: gpt-oss-20b 90 (The chat template earns 20, a Jinja file in the repository.); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)
- Reach, gpt-oss-20b +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…); Hy-Memory-30B-A3B 85 (Memory 25, Tencent's own Q4_K_M GGUF is 18.24 GB, and 18.24 GB × 1.2 = 21.9 GB, which fits 24 GB but not 16 GB.)