# BigBang-v1 vs Hy-Memory-30B-A3B (slim)

> Hy-Memory-30B-A3B scores 61 (C) to BigBang-v1's 56.3 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/bigbang-v1-vs-hy-memory-30b-a3b.md (~9,300 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/bigbang-v1-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/bigbang-v1-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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Hy-Memory-30B-A3B scores 61 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in every scored category. Both do open-weight models you run yourself.

- BigBang-v1: C 56.3, rank #116 of 160 open-weight models · https://www.anchorterminal.com/tools/bigbang-v1.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
- BigBang-v1, good for Agents with 96 GB or more that want an Apache 2.0 mixture-of-experts model tuned for research, search and coding, and can do without publisher support.
- 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 60; Risk, 60 against 55; Agent interface, 65 against 60; Documentation and upkeep, 68 against 46.

| Category | BigBang-v1 | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 60 | 65 |
| Documentation and upkeep (10%) | 46 | 68 |

| Fact (where they differ) | BigBang-v1 | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | The Endless Frontier (endless-frontier) | Tencent (Hy team) |
| Last release | 2026-08-06 | 2026-10-16 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, Hy-Memory-30B-A3B +25: BigBang-v1 60 (Memory 10 of 30, the only build from the publisher is BF16 at 71.9 GB, 86.3 GB with a fifth added, which fits the reference machine but not 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.)
- Documentation and upkeep, Hy-Memory-30B-A3B +22: BigBang-v1 46 (Model card 11 of 20, limitations, architecture and a cut-off are missing.); 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, Hy-Memory-30B-A3B +5: BigBang-v1 55 (File safety 25, safetensors only and nothing from the repository runs.); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)
- Agent interface, Hy-Memory-30B-A3B +5: BigBang-v1 60 (Chat template 20, the base's template in the repository.); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)