# Hy-Memory-30B-A3B vs ThinkingCap (Qwen3.8 27B) (slim)

> Hy-Memory-30B-A3B and ThinkingCap score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-thinkingcap-qwen3-8-27b.md (~10,300 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-thinkingcap-qwen3-8-27b.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-thinkingcap-qwen3-8-27b
- 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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Hy-Memory-30B-A3B and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on agent interface. Both do open-weight models you run yourself.

- Hy-Memory-30B-A3B: C 61, rank #68 of 160 open-weight models · https://www.anchorterminal.com/tools/hy-memory-30b-a3b.min.md
- ThinkingCap (Qwen3.8 27B): C 61, rank #58 of 160 open-weight models · https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.min.md
- 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 Reach, 85 against 75; Risk, 60 against 45; Documentation and upkeep, 68 against 53.
- ThinkingCap (Qwen3.8 27B), good for Small teams and individuals running Qwen3.8-27B for agent or reasoning work who want shorter thinking traces on one 24 GB GPU or Mac. Ahead on Agent interface, 70 against 65.

| Category | Hy-Memory-30B-A3B | ThinkingCap (Qwen3.8 27B) |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 75 |
| Risk (20%) | 60 | 45 |
| Agent interface (10%) | 65 | 70 |
| Documentation and upkeep (10%) | 68 | 53 |

| Fact (where they differ) | Hy-Memory-30B-A3B | ThinkingCap (Qwen3.8 27B) |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | BottleCap AI |
| Licence | Apache-2.0 | PolyForm-Small-Business-1.0.0 |
| Last release | 2026-10-16 | 2026-10-06 |
| Privacy policy last updated | no document linked | 2026-01-21 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Risk, Hy-Memory-30B-A3B +15: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); ThinkingCap (Qwen3.8 27B) 45 (File safety 25, safetensors only and no code in the repository.)
- Documentation and upkeep, Hy-Memory-30B-A3B +15: 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)…); ThinkingCap (Qwen3.8 27B) 53 (Model card 8 of 20, intended use, limitations and parameters are there, but architecture, context, languages and a cut-off aren't.)
- Reach, Hy-Memory-30B-A3B +10: 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.); ThinkingCap (Qwen3.8 27B) 75 (Memory 25 of 30, BottleCap's IQ4_XS GGUF is 15.5 GB, 18.6 GB with a fifth added, which fits 24 GB.)
- Agent interface, ThinkingCap (Qwen3.8 27B) +5: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); ThinkingCap (Qwen3.8 27B) 70 (Chat template 20, the same Jinja template as Qwen3.8-27B, in the repository.)