Inquiry About HF Spaces Usage — Multi-GPU Deployment Requirements

A user inquired about deploying a multi-GPU environment on Hugging Face Spaces, requesting 8 GPUs with over 40GB VRAM each to run a generative model and a vLLM model. The user asked about configuration, hardware tiers, resource splitting, and pricing for such a setup.

Dear Hugging Face Team, I hope this email finds you well. I am writing to inquire about deploying a multi-GPU environment on Hugging Face Spaces. Specifically, my requirements are as follows: - I need a GPU environment with 8 GPUs , each with more than 40GB of VRAM per card. - Of these 8 GPUs, I plan to allocate 4 GPUs for deploying a generative model . - The remaining 4 GPUs will be used to deploy a vLLM model . Could you please advise on the following: - What is the recommended way to configure and deploy such a multi-GPU 8x GPU Space on Hugging Face? - Which GPU hardware tiers/instances on Spaces would meet the requirement of 40GB VRAM per card? - Are there any specific configuration steps or best practices for splitting GPU resources across two different model deployments 4 GPUs for the generative model and 4 GPUs for vLLM within the same Space, or would this require separate Spaces? - Are there any pricing details or quota limitations I should be aware of for this kind of setup? I would greatly appreciate your guidance on how to proceed with this deployment. Please let me know if you need any additional information about my use case. Thank you very much for your time and support.