LFM2.5-8B-A1B, an edge model built for fast, reliable tool calling on consumer hardware.
115.8K Pulls 5 Tags Updated 2 months ago
LFM2.5 is a new family of hybrid models designed for on-device deployment.
1.3M Pulls 5 Tags Updated 6 months ago
LFM2.5-2.6B By LiquidAI
67 Pulls 1 Tag Updated 5 days ago
LFM2.5-2.6B by Liquid AI — deploy agents everywhere. A 2.6B dense reasoning model (Q4_K_M, ~1.7 GB) with native tool calling, 128K context, and 16-language support. Runs on any 8 GB GPU.
902 Pulls 1 Tag Updated 1 week ago
LFM2.5-350M & LFM2.5-8B-A1B is a fast, memory-efficient hybrid MoE language model. Unsloth Dynamic (UD) quants available.
1,632 Pulls 15 Tags Updated 1 month ago
580 Pulls 2 Tags Updated 5 months ago
LFM2.5-230M is a hybrid language model by Liquid AI, Built to Run Anywhere. The ideal lightweight AI companion for: 4 GB laptops · 8 GB desktops · Edge devices · Raspberry Pi 5
272 Pulls 1 Tag Updated 3 weeks ago
Optimized for mobile use via Termux
10 Pulls 1 Tag Updated 1 week ago
Source: https://huggingface.co/LiquidAI/LFM2.5-350M-GGUF
308 Pulls 1 Tag Updated 4 months ago
Source: https://huggingface.co/FlameF0X/LFM2.5-1.2B-Distilled-Claude-4.6-GGUF?local-app=ollama
263 Pulls 1 Tag Updated 4 months ago
LFM2.5-8B-A1B Q8_0 with working tool calls — fixes the llama.cpp parser crash (#23838). Same weights, metadata-only fix.
159 Pulls 2 Tags Updated 2 months ago
Source: https://huggingface.co/mradermacher/LFM2.5-1.2B-MEGABRAIN2-Thinking-Kimi-V2-DISTILL-GGUF
241 Pulls 1 Tag Updated 5 months ago
215 Pulls 1 Tag Updated 4 months ago
LFM 2.5 Instruct is a nothink version of LFM2.5-Thinking
96 Pulls 3 Tags Updated 3 months ago
Agentic coding fine-tune of LFM2.5-8B-A1B for the Klide runtime — makes correct edits, verifies, and stops instead of looping. LFM Open License v1.0.
60 Pulls 1 Tag Updated 1 month ago
https://huggingface.co/LiquidAI/LFM2.5-VL-450M
85 Pulls 1 Tag Updated 3 months ago
66 Pulls 1 Tag Updated 5 months ago
3,942 Pulls 10 Tags Updated 6 months ago
LFM2.5 is a new family of hybrid models designed for on-device deployment. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.
2,026 Pulls 4 Tags Updated 6 months ago
1,386 Pulls 5 Tags Updated 6 months ago