# LFM2.5-2.6B vs Nanbeige4.2-3B (slim)

> Nanbeige4.2-3B 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/lfm2-5-2-6b-vs-nanbeige-4-2-3b.md (~9,650 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-nanbeige-4-2-3b.json · canonical https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-nanbeige-4-2-3b
- 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)

Nanbeige4.2-3B scores 61 (C) on agent readiness against LFM2.5-2.6B's 50.3 (D), and leads in 3 of 4 scored categories. LFM2.5-2.6B leads on reach. Both do open-weight models you run yourself.

- 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
- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.min.md
- 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.
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU Ahead on Risk, 55 against 50; Agent interface, 85 against 75; Documentation and upkeep, 72 against 57.

| Category | LFM2.5-2.6B | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 85 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 57 | 72 |

| Fact (where they differ) | LFM2.5-2.6B | Nanbeige4.2-3B |
| --- | --- | --- |
| Vendor | Liquid AI | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-09-11 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Nanbeige4.2-3B +15: LFM2.5-2.6B 57 (The model card earns 17, with everything but a knowledge cut-off.); Nanbeige4.2-3B 72 (Model card 17, Intended use, limitations, the architecture, the parameters (3B outside the embeddings), the context and the languages (in the metadata) are on t…)
- Agent interface, Nanbeige4.2-3B +10: LFM2.5-2.6B 75 (The chat template earns 20 for chat_template.jinja in the repository.); Nanbeige4.2-3B 85 (Chat template 20, A Jinja chat template in tokenizer_config.json (7,961 characters), with enable_thinking, preserve_thinking, tools and tool_call_format switche…)
- Reach, LFM2.5-2.6B +5: 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.); Nanbeige4.2-3B 85 (Memory 30, the smallest build from Nanbeige is the FP8 repository (the 8-bit GPTQ one is the same size), 5.19 GB, and 5.19 GB × 1.2 = 6.2 GB, within 16 GB.)
- Risk, Nanbeige4.2-3B +5: 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.); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)