WIDEAREAINTELLIGENCE
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huggingface

LFM2.5 2.6B

hf/LiquidAI/LFM2.5-2.6B-GGUF

↓ runs free on your own hardware

Open-weight model — runs free on your own GPU via the node runtime (GGUF). 841,972 downloads and 381 likes on Hugging Face (LiquidAI/LFM2.5-2.6B-GGUF).

specs & pricing
Type
text
Provider
huggingface
Model ID
hf/LiquidAI/LFM2.5-2.6B-GGUF
Self-hostable
Yes — runs on your own GPU

Listed in the directory for discovery. textmodels aren't callable through the chat gateway yet — image and video models can run on your own nodes today.

Run it on your own hardware

Estimated GPU memory for LFM2.5 2.6B (2.6B parameters), for the weights alone — add room for the context cache.

Q4_K_M
~2.2 GBfits a 8 GB card
Q8_0
~3.3 GBfits a 8 GB card
FP16 / BF16
~5.6 GBfits a 8 GB card

Install the agent on the machine and it dials out to the gateway over a single WebSocket — no port forwarding or inbound firewall rules. Requests for this model go to your node first and fail over to the cloud only when it can't serve.

VRAM calculator →Which GPU do I need? →

/// initialize

Call LFM2.5 2.6B through one OpenAI-compatible endpoint.

Serve it from hardware you own, with cloud failover when your nodes are busy or offline.

Run it on your own hardware

no credit card · 2 nodes free · openai-compatible

Frequently asked questions

Can I run LFM2.5 2.6B on my own hardware?
Yes — LFM2.5 2.6B is an open-weight model you can run on a workstation or on-prem server you own. At Q4_K_M it needs roughly 2.2 GB of GPU memory, plus room for the context cache — it fits a single 8 GB card. Wide Area Intelligence routes requests to your own nodes first and fails over to the cloud only when they can't serve.

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