# EXAONE 4.5 33B vs Hy-Memory-30B-A3B (slim)

> EXAONE 4.5 33B 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/exaone-4-5-33b-vs-hy-memory-30b-a3b.md (~10,050 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy-memory-30b-a3b.json · canonical https://www.anchorterminal.com/compare/exaone-4-5-33b-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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EXAONE 4.5 33B 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.

- EXAONE 4.5 33B: C 61, rank #61 of 160 open-weight models · https://www.anchorterminal.com/tools/exaone-4-5-33b.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
- EXAONE 4.5 33B, good for Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights 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 65; Risk, 60 against 50; Documentation and upkeep, 68 against 50.

| Category | EXAONE 4.5 33B | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 65 | 85 |
| Risk (20%) | 50 | 60 |
| Agent interface (10%) | 85 | 65 |
| Documentation and upkeep (10%) | 50 | 68 |

| Fact (where they differ) | EXAONE 4.5 33B | Hy-Memory-30B-A3B |
| --- | --- | --- |
| Vendor | LG AI Research | Tencent (Hy team) |
| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | Apache-2.0 |
| Last release | 2026-07-06 | 2026-10-16 |
| Terms last updated | not read yet | no document linked |

Why the edge:
- Reach, Hy-Memory-30B-A3B +20: EXAONE 4.5 33B 65 (Memory 20, the smallest build at 4 bits is LG's IQ4_XS GGUF, 18.03 GB with the 2.57 GB projector, and 20.60 GB × 1.2 = 24.7 GB, within 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.)
- Agent interface, EXAONE 4.5 33B +20: EXAONE 4.5 33B 85 (Chat template 20, chat_template.jinja in the repository (5,930 characters).); Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.)
- Documentation and upkeep, Hy-Memory-30B-A3B +18: EXAONE 4.5 33B 50 (Model card 20, Uses (the quickstart's question answering, document and agent examples), limitations, the architecture, the parameters, the context, the language…); 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 +10: EXAONE 4.5 33B 50 (File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository.); Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.)