WIDEAREAINTELLIGENCE
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huggingface

Mistral 7B Instruct v0.1

hf/TheBloke/Mistral-7B-Instruct-v0.1-GGUF

↓ runs free on your own hardware⚙ tool calling

Open-weight model — runs free on your own GPU via the node runtime (GGUF). 31,726 downloads and 614 likes on Hugging Face (TheBloke/Mistral-7B-Instruct-v0.1-GGUF).

specs & pricing
Type
text
Provider
huggingface
Model ID
hf/TheBloke/Mistral-7B-Instruct-v0.1-GGUF
Capabilities
tools
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 Mistral 7B Instruct v0.1 (7.0B parameters), for the weights alone — add room for the context cache.

Q4_K_M
~4.7 GBfits a 8 GB card
Q8_0
~7.7 GBfits a 8 GB card
FP16 / BF16
~13.8 GBfits a 16 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 Mistral 7B Instruct v0.1 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 Mistral 7B Instruct v0.1 on my own hardware?
Yes — Mistral 7B Instruct v0.1 is an open-weight model you can run on a workstation or on-prem server you own. At Q4_K_M it needs roughly 4.7 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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