LFM2.5-24B-A2B
FP8 · vllm · 128K context · RTX PRO 6000 Blackwell · 96 GB
Liquid AI's 24B hybrid mixture-of-experts (about 2B active; 30 short-convolution and 10 attention layers, 64 experts). It reasons before it answers and calls tools.
272 tok/sdecode
12,251 tok/sprefill
128Kcontext window
Tested on this cardOct 30, 2026
Follow the steps below to download and run this recipe. Omarchy Local AI lists the recipes it can launch on your hardware. The server then answers on http://localhost:8000/v1.
- 1 Download the weights
hf download LiquidAI/LFM2.5-24B-A2B-FP8 \ --revision f54bf39547fd5b7955abb9fe8d1b151e31fbbddb \ --local-dir ~/models/LFM2.5-24B-A2B-FP8-f54bf395
- 2 Start the server
docker run --rm \ --gpus all \ -p 8000:8000 \ --shm-size 16g \ -v ~/models/LFM2.5-24B-A2B-FP8-f54bf395:/models/LFM2.5-24B-A2B-FP8-f54bf395:ro \ --entrypoint vllm \ vllm/vllm-openai:v0.30.0@sha256:8a69ffad015f138d7170c4ddc429e230a3bc1c1719f67e14324749df200a4b90 \ serve \ /models/LFM2.5-24B-A2B-FP8-f54bf395 \ --served-model-name LFM2.5-24B-A2B-FP8-f54bf395 \ --host 0.0.0.0 \ --port 8000 \ --max-model-len 131072 \ --max-num-seqs 1 \ --gpu-memory-utilization 0.9 \ --kv-cache-dtype auto \ --enable-auto-tool-choice \ --tool-call-parser lfm2 \ --reasoning-parser deepseek_r1
✓ loadLoads and serves within an hour
✓ chatAnswers a plain question and stops on its own
✓ reasoningThinks separately and gets 17 × 23 right
✓ toolsCalls a tool with the right arguments and uses the result
✓ contextRecalls a code buried in a prompt that fills 85% of the window
✓ speedDecodes at 15 tok/s or more
Passed all six checks on a real RTX PRO 6000 Blackwell WS (450 W cap) on Oct 30, 2026.
- Weights
- LiquidAI/LFM2.5-24B-A2B-FP8 @ f54bf39547 ›
- Image
- vllm/vllm-openai:v0.30.0@sha256:8a69ffad015f138d7170c4ddc429e230a3bc1c1719f67e14324749df200a4b90
- Engine profile
- vllm ›
- Recipe file
- registry/recipes/nvidia/rtx-pro-6000-blackwell-96gb/lfm2.5-24b-a2b.vllm.128k.json ›
- Model released
- Oct 12, 2026
- Tested
- owner, RTX PRO 6000 Blackwell WS (450 W cap)