AtomicChat / text-generation Open weights updated 1 week ago

LFM2.5-24B-A2B-Uncensored-GGUF

Liquid's refusal behaviour projected out of the original weights, in the second two thirds of the network only. Shipped two ways: six baked GGUF builds, and a 24 MB LoRA adapter for the LFM2.5-24B-A2B quants you already have. The measurements behind this card are public. Built by the team behind Atomic Chat, the app that runs open-weight models locally and offline. On held-out prompts, refusals fall from 96.3% to 1.2...

Params
24.0 B
Context
131,072
Downloads 30d
639 K
Likes
77
Licence: other Not gated GGUF 10 languages View on Hugging Face ↗

Download history

daily snapshots · 13 days
639 K151 K
Oct 29Nov 2Nov 6Nov 10

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-Uncensored-LoRA.gguf GGUF 0.0 GB 4.1 GB ✅ Runs comfortably
LFM2.5-24B-A2B-Uncensored-AD-IQ3_M.gguf IQ3_M 12.1 GB 17.4 GB ✅ Runs comfortably
LFM2.5-24B-A2B-Uncensored-AD-IQ4_XS.gguf IQ4_XS 14.5 GB 20.0 GB ⚠️ Tight — reduce context
LFM2.5-24B-A2B-Uncensored-AD-Q4_K_M.gguf Q4_K_M 15.4 GB 21.0 GB ⚠️ Tight — reduce context
LFM2.5-24B-A2B-Uncensored-AD-Q5_K_M.gguf Q5_K_M 17.3 GB 23.1 GB ⚠️ Tight — reduce context
LFM2.5-24B-A2B-Uncensored-AD-Q6_K.gguf Q6_K 20.9 GB 27.1 GB ❌ Won’t fit
LFM2.5-24B-A2B-Uncensored-AD-Q8_0.gguf Q8_0 25.7 GB 32.4 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-uncensored-gguf

# pin the quantization explicitly
$ ollama run lfm2-5-24b-a2b-uncensored-gguf-q4_k_m
est. VRAM 21.0 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
2026-10-29

Family

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

Compare with any text-generation model