# Hy-Memory-30B-A3B vs Qwen3-VL-32B-Instruct (slim)

> Hy-Memory-30B-A3B scores 61 (C) to Qwen3-VL-32B-Instruct's 56.4 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen3-vl-32b-instruct.md (~9,750 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen3-vl-32b-instruct.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-qwen3-vl-32b-instruct
- 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 Qwen3-VL-32B-Instruct's 56.4 (C), and leads in 3 of 4 scored categories. 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
- Qwen3-VL-32B-Instruct: C 56.4, rank #115 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct.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 Risk, 60 against 55; Agent interface, 65 against 60; Documentation and upkeep, 68 against 31.
- Qwen3-VL-32B-Instruct, good for An agent with a 32 GB GPU or more that wants the largest dense Qwen3-VL model for images, documents and video

| Category | Hy-Memory-30B-A3B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 85 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 65 | 60 |
| Documentation and upkeep (10%) | 68 | 31 |

| Fact (where they differ) | Hy-Memory-30B-A3B | Qwen3-VL-32B-Instruct |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | Alibaba (Qwen team) |
| Last release | 2026-10-16 | 2025-11-01 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +37: 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)…); Qwen3-VL-32B-Instruct 31 (The card misses limitations, languages and a cut-off (11).)
- Risk, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); Qwen3-VL-32B-Instruct 55 (Safetensors and GGUF only and no code in the repositories, so the FP8 card's trust_remote_code flag runs nothing (25).)
- Agent interface, Hy-Memory-30B-A3B +5: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); Qwen3-VL-32B-Instruct 60 (A Jinja chat template in the repository (20).)