LiquidAI/LFM2.5-24B-A2B

Gguf's: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Free Demo: https://playground.liquid.ai "LFM2.5-24B-A2B is a 24B-parameter reasoning model with only 2B active parameters, built for fast, private agents on-device. It is the largest and final model in the LFM2.5 family, which now spans two orders of magnitude: from LFM2.5-230M to LFM2.5-24B-A2B. Best-in-class agent: Competitive with Qwen3.6-35B-A3B, a model with ~50% more total and active parameters, on agentic and tool-use tasks, scoring 48.09 on LiveClaw versus 38.19. Reasoning at MoE speed: Always thinks before it answers. With only 2B active parameters per token, each reasoning token is cheap. Efficient inference: Runs up to 1.7× faster than comparable MoEs on-device, with 184 tok/s on an Apple M5 Max and up to 21K output tok/s on a single NVIDIA B300 GPU. LFM2.5-24B-A2B is a general-purpose text-only reasoning model with the following features: Total parameters: 24.0B Active parameters: 2.45B Number of layers: 40 (30 double-gated short convolution blocks + 10 GQA) Experts: 64 per MoE block, top-4 routing Training budget: 36 trillion tokens Vocabulary size: 128,000 Context length: 131,072 tokens Languages: English, Arabic, Chinese, French, German, Italian, Japanese, Korean, Portuguese, Spanish, Vietnamese, Thai, Indonesian, Hindi, Russian, Polish Generation parameters: temperature: 0.1 top_k: 50 repetition_penalty: 1.05" submitted by /u/Skyline34rGt [link] [comments]

Related

• d1-3B and d1-omni from LiquidAI
• A 2.6B model with tool calling and 128K context now runs at 30 tok/s on a phone
• Release b11003 · ggml-org/llama.cpp

Source: r/LocalLLaMA | 2026-10-13