# Darwin-36B-Opus vs Hy-Memory-30B-A3B (slim)

> Darwin-36B-Opus and Hy-Memory-30B-A3B 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/darwin-36b-opus-vs-hy-memory-30b-a3b.md (~9,900 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/darwin-36b-opus-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/darwin-36b-opus-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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Darwin-36B-Opus and Hy-Memory-30B-A3B score within a point of each other on agent readiness, 61 (C) and 61 (C). Hy-Memory-30B-A3B leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- Darwin-36B-Opus: C 61, rank #43 of 160 open-weight models · https://www.anchorterminal.com/tools/darwin-36b-opus.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
- Darwin-36B-Opus, good for Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required Ahead on Agent interface, 70 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 Reach, 85 against 80; Risk, 60 against 55; Documentation and upkeep, 68 against 61.

| Category | Darwin-36B-Opus | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 85 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 70 | 65 |
| Documentation and upkeep (10%) | 61 | 68 |

| Fact (where they differ) | Darwin-36B-Opus | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | FINAL-Bench (VIDRAFT) | Tencent (Hy team) |
| Last release | 2026-04-23 | 2026-10-16 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +7: Darwin-36B-Opus 61 (Model card 11, it covers architecture, parameters, context and languages but not intended use, limitations or a knowledge cut-off.); 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)…)
- Reach, Hy-Memory-30B-A3B +5: Darwin-36B-Opus 80 (Memory 20, the publisher's Q4_K_M GGUF is 21.2 GB and needs about 25.4 GB with the fifth added, so 32 GB.); 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.)
- Risk, Hy-Memory-30B-A3B +5: Darwin-36B-Opus 55 (File safety 25, safetensors and GGUF only with no code in the repository, so the card's trust_remote_code flag loads nothing extra.); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)
- Agent interface, Darwin-36B-Opus +5: Darwin-36B-Opus 70 (Chat template 20, Qwen3.6's Jinja template in the repository.); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)