Deploy local agents everywhere with LFM2.5-2.6B
It supports tool calling and multi-step workflows while staying small and fast enough for everyday hardware, from laptops to phones. This enables developers to deploy agents everywhere, keep data private on the device, and scale usage without a cloud inference bill. Best-in-class agent: Competitive with models 4x larger on tool use, instruction following, and multi-step agentic tasks.
- ▪It supports tool calling and multi-step workflows while staying small and fast enough for everyday hardware, from laptops to phones.
- ▪This enables developers to deploy agents everywhere, keep data private on the device, and scale usage without a cloud inference bill.
- ▪Best-in-class agent: Competitive with models 4x larger on tool use, instruction following, and multi-step agentic tasks.
Hugging Face Blog files mainly under ai. We currently carry 26 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Hugging Face - Blog |
| Canonical URL | https://huggingface.co/blog/LiquidAI/lfm2-5-2-6b |
| Publication time | Tue, 04 Aug 2026 13:58:29 GMT |
| Retrieval time | 2026-08-04T13:59:34.906Z |
| Last seen | 2026-08-04T13:59:34.906Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 1bQZEAzAd5YA · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Back to Articles Deploy local agents everywhere with LFM2.5-2.6B Team Article Published August 4, 2026 Upvote 1 Leonie Monigatti iamleonie Follow LiquidAI Sergei Tilga tilgasergey Follow LiquidAI Sinoué GAD GAD-cell Follow LiquidAI Song Duong sduong Follow LiquidAI Tim Seyde tseyde Follow LiquidAI Maxime Labonne mlabonne Follow LiquidAI How we built a reliable agentic model for edge devices Benchmark results Inference speed on CPU and GPU How to use LFM2.5-2.6B LFM2.5-2.6B demo Get Started Citation LFM2.5-2.6B is built to power capable agents entirely on-device. It supports tool calling and multi-step workflows while staying small and fast enough for everyday hardware, from laptops to phones.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hugging Face - Blog.
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