# GLM-4.7-Flash vs Hy-Memory-30B-A3B (slim)

> GLM-4.7-Flash scores 63 (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/glm-4-7-flash-vs-hy-memory-30b-a3b.md (~9,700 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/glm-4-7-flash-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/glm-4-7-flash-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)

GLM-4.7-Flash scores 63 (B) on agent readiness against Hy-Memory-30B-A3B's 61 (C), and leads in 1 of 4 scored categories. Hy-Memory-30B-A3B leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.

- GLM-4.7-Flash: B 63, rank #26 of 160 open-weight models · https://www.anchorterminal.com/tools/glm-4-7-flash.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
- GLM-4.7-Flash, good for Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime Ahead on Agent interface, 85 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 28.

| Category | GLM-4.7-Flash | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 85 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 85 | 65 |
| Documentation and upkeep (10%) | 28 | 68 |

| Fact (where they differ) | GLM-4.7-Flash | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Tencent (Hy team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-01-29 | 2026-10-16 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +40: GLM-4.7-Flash 28 (The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 0, as the card describes none.); 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)…)
- Agent interface, GLM-4.7-Flash +20: GLM-4.7-Flash 85 (A Jinja chat template sits in the repository, for 20. The tool-calling format is the full 25, because Z.ai itself names the glm47 parser for vLLM and SGLang, sa…); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)
- Reach, Hy-Memory-30B-A3B +5: GLM-4.7-Flash 80 (Memory earns 25, since Ollama's smallest build is the 19 GB q4_K_M one, about 22.8 GB with the fifth added, which fits 24 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: GLM-4.7-Flash 55 (File safety is full, with safetensors only and the card loading it through Transformers' own code without remote code.); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)