# Hy-Memory-30B-A3B vs LFM2.5-2.6B (slim)

> Hy-Memory-30B-A3B scores 61 (C) to LFM2.5-2.6B's 50.3 (D) 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-lfm2-5-2-6b.md (~9,600 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm2-5-2-6b.json · canonical https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm2-5-2-6b
- 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 LFM2.5-2.6B's 50.3 (D), and leads in 2 of 4 scored categories. LFM2.5-2.6B leads on reach and agent interface. 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
- LFM2.5-2.6B: D 50.3, rank #146 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm2-5-2-6b.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 50; Documentation and upkeep, 68 against 57.
- LFM2.5-2.6B, good for Agents that want a small local helper for tool calls, extraction and RAG on a laptop, phone or CPU, at organisations under the licence's revenue threshold Ahead on Reach, 90 against 85; Agent interface, 75 against 65.

| Category | Hy-Memory-30B-A3B | LFM2.5-2.6B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 90 |
| Risk (20%) | 60 | 50 |
| Agent interface (10%) | 65 | 75 |
| Documentation and upkeep (10%) | 68 | 57 |

| Fact (where they differ) | Hy-Memory-30B-A3B | LFM2.5-2.6B |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | Liquid AI |
| Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-10-16 | 2026-11-03 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Documentation and upkeep, Hy-Memory-30B-A3B +11: 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)…); LFM2.5-2.6B 57 (The model card earns 17, with everything but a knowledge cut-off.)
- Risk, Hy-Memory-30B-A3B +10: Hy-Memory-30B-A3B 60 (File safety 25, 51 safetensors shards and no pickle or Python files.); LFM2.5-2.6B 50 (File safety earns 25, safetensors and GGUF only, and nothing from the repository runs to load it or build prompts.)
- Agent interface, LFM2.5-2.6B +10: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); LFM2.5-2.6B 75 (The chat template earns 20 for chat_template.jinja in the repository.)
- Reach, LFM2.5-2.6B +5: 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.); LFM2.5-2.6B 90 (Memory earns the full 30, since Liquid's own 4-bit GGUF is 1.59 GB and fits 8 GB with room to spare.)