# LFM3-1.7B vs Nemotron 3 Nano 4B (slim)

> LFM3-1.7B scores 61 (C) to Nemotron 3 Nano 4B's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b.md (~9,750 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b.json · canonical https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b
- 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)

LFM3-1.7B scores 61 (C) on agent readiness against Nemotron 3 Nano 4B's 56.8 (C), and leads in 2 of 4 scored categories. Nemotron 3 Nano 4B leads on reach and risk. Both do open-weight models you run yourself.

- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.min.md
- Nemotron 3 Nano 4B: C 56.8, rank #110 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-4b.min.md
- 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 Agent interface, 100 against 70; Documentation and upkeep, 67 against 55.
- Nemotron 3 Nano 4B, good for Agents on laptops, edge boards and small GPUs that need a cheap local tool-calling helper in English Ahead on Reach, 90 against 85; Risk, 65 against 40.

| Category | LFM3-1.7B | Nemotron 3 Nano 4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 90 |
| Risk (20%) | 40 | 65 |
| Agent interface (10%) | 100 | 70 |
| Documentation and upkeep (10%) | 67 | 55 |

| Fact (where they differ) | LFM3-1.7B | Nemotron 3 Nano 4B |
| --- | --- | --- |
| Vendor | Liquid AI | NVIDIA |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | NVIDIA Nemotron Open Model License |
| llms.txt | yes | no |
| Last release | 2026-11-09 | 2026-03-16 |
| Agent reviews | none | 3.3/5 (4) |

Why the edge:
- Agent interface, LFM3-1.7B +30: 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.); Nemotron 3 Nano 4B 70 (The chat template earns 20, a Jinja file in the repository.)
- Risk, Nemotron 3 Nano 4B +25: LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Nemotron 3 Nano 4B 65 (File safety earns 15, safetensors and GGUF only but with 10 off because the documented commands pass trust_remote_code and load a parser plugin from the reposit…)
- Documentation and upkeep, LFM3-1.7B +12: 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…); Nemotron 3 Nano 4B 55 (The model card earns 20, all seven items with limitations in the linked subcard.)
- Reach, Nemotron 3 Nano 4B +5: 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.); Nemotron 3 Nano 4B 90 (Memory earns the full 30, since NVIDIA's own 2.84 GB GGUF needs under 4 GB with the fifth added.)