WIDEAREAINTELLIGENCE
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huggingface

bitnet b1.58 2B 4T

hf/microsoft/bitnet-b1.58-2B-4T-gguf

↓ runs free on your own hardware

Open-weight model — runs free on your own GPU via the node runtime (GGUF). 17,036 downloads and 296 likes on Hugging Face (microsoft/bitnet-b1.58-2B-4T-gguf).

specs & pricing
Type
text
Provider
huggingface
Model ID
hf/microsoft/bitnet-b1.58-2B-4T-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 bitnet b1.58 2B 4T (2.0B parameters), for the weights alone — add room for the context cache.

Q4_K_M
~1.9 GBfits a 8 GB card
Q8_0
~2.7 GBfits a 8 GB card
FP16 / BF16
~4.5 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 bitnet b1.58 2B 4T 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 bitnet b1.58 2B 4T on my own hardware?
Yes — bitnet b1.58 2B 4T is an open-weight model you can run on a workstation or on-prem server you own. At Q4_K_M it needs roughly 1.9 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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