LiquidAI / text-generation Open weights updated 1 week ago

LFM2.5-24B-A2B-GGUF

LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.

Params
24.0 B
Context
131,072
Downloads 30d
177 K
Likes
239
Licence: other Not gated GGUF 10 languages View on Hugging Face ↗

Download history

tracking started — chart appears after 7 days of snapshots (4 recorded)
177 K downloads in the last 30 days

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
LFM2.5-24B-A2B-QAD-Q4_0.gguf Q4_0 13.6 GB 19.0 GB ✅ Runs comfortably
LFM2.5-24B-A2B-Q4_K_M.gguf Q4_K_M 14.5 GB 20.1 GB ⚠️ Tight — reduce context
LFM2.5-24B-A2B-Q5_K_M.gguf Q5_K_M 17.0 GB 22.8 GB ⚠️ Tight — reduce context
LFM2.5-24B-A2B-Q6_K.gguf Q6_K 19.7 GB 25.8 GB ❌ Won’t fit
LFM2.5-24B-A2B-Q8_0.gguf Q8_0 25.5 GB 32.1 GB ❌ Won’t fit
LFM2.5-24B-A2B-BF16.gguf GGUF 48.0 GB 56.9 GB ❌ Won’t fit
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · Q4_K_M
$ ollama run lfm2-5-24b-a2b-gguf

# pin the quantization explicitly
$ ollama run lfm2-5-24b-a2b-gguf-q4_k_m
est. VRAM 20.1 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
24.0 B
Context length
131,072
Licence
other
First seen on the Hub
2026-10-09
Base model
LFM2.5-24B-A2B
Training datasets
undisclosed
Added to our catalog
2026-10-22

Family

Base model and the most-downloaded derivatives in the catalog.

Compare with any text-generation model