# Hy3 vs LFM3-1.7B (slim)

> Hy3 scores 62.6 (B) to LFM3-1.7B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Hy3 scores 62.6 (B) on agent readiness against LFM3-1.7B's 61 (C), and leads in 1 of 4 scored categories. LFM3-1.7B leads on reach, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- Hy3: B 62.6, rank #28 of 160 open-weight models · https://www.anchorterminal.com/tools/hy3.min.md
- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.min.md
- Hy3, good for Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0 Ahead on Risk, 60 against 40.
- LFM3-1.7B, good for Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits Ahead on Reach, 85 against 70; Agent interface, 100 against 75; Documentation and upkeep, 67 against 56.

| Category | Hy3 | LFM3-1.7B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 85 |
| Risk (20%) | 60 | 40 |
| Agent interface (10%) | 75 | 100 |
| Documentation and upkeep (10%) | 56 | 67 |

| Fact (where they differ) | Hy3 | LFM3-1.7B |
| --- | --- | --- |
| 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 | 2026-07-20 | 2026-11-09 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Agent interface, LFM3-1.7B +25: Hy3 75 (The chat template earns 20, a chat_template.jinja in the repository.); LFM3-1.7B 100 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch.)
- Risk, Hy3 +20: Hy3 60 (File safety earns the full 25, safetensors only with no pickle files, and the documented route runs vLLM or SGLang from their own code with a Jinja template, so…); LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)
- Reach, LFM3-1.7B +15: Hy3 70 (Memory earns 5, because the smallest build of 4-bit precision or better is AngelSlim's GPTQ-Int4 of 168.5 GB, about 202 GB with the fifth added, which is within…); LFM3-1.7B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line.)
- Documentation and upkeep, LFM3-1.7B +11: Hy3 56 (The model card earns 11, covering intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off.); LFM3-1.7B 67 (Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-ste…)