# Cola2 vs Hy-Memory-30B-A3B (slim)

> Hy-Memory-30B-A3B scores 61 (C) to Cola2's 33.9 (F) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/cola2-vs-hy-memory-30b-a3b.md (~9,150 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/cola2-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/cola2-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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Hy-Memory-30B-A3B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in every scored category. Both do open-weight models you run yourself.

- Cola2: F 33.9, rank #160 of 160 open-weight models · https://www.anchorterminal.com/tools/cola2.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
- Cola2, good for Researchers working on latent or diffusion language models who want a checkpoint to study
- 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 25; Risk, 60 against 40; Agent interface, 65 against 20; Documentation and upkeep, 68 against 58.

| Category | Cola2 | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 25 | 85 |
| Risk (20%) | 40 | 60 |
| Agent interface (10%) | 20 | 65 |
| Documentation and upkeep (10%) | 58 | 68 |

| Fact (where they differ) | Cola2 | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | ByteDance (Seed) | Tencent (Hy team) |
| Licence | None stated for the weights (the code is Apache 2.0) | Apache-2.0 |
| Last release | 2026-11-06 | 2026-10-16 |

Why the edge:
- Reach, Hy-Memory-30B-A3B +60: Cola2 25 (Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 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.)
- Agent interface, Hy-Memory-30B-A3B +45: Cola2 20 (Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer.); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)
- Risk, Hy-Memory-30B-A3B +20: Cola2 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)
- Documentation and upkeep, Hy-Memory-30B-A3B +10: Cola2 58 (Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model c…); 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)…)