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    Which workloads fit an off-grid RTX GPU unit?

    A builder developing a unit with two RTX PRO 6000 GPUs per node asks renters about their workflows.

    Danielle Fong 🔆DF
    Sid RavikumarSR
    2 Sources, ,

    TLDR

    A builder says they're developing an off-grid compute unit with two RTX PRO 6000 GPUs per node. They want to hear from people renting RTX GPUs rather than B300 or H200 clusters, especially for workloads needing no more than 96GB of VRAM per GPU, high-bandwidth GPU links or exceptionally fast, low-latency internet. They suggest smaller-model inference, robotics simulation, fine-tuning and rendering as possible uses.

    Combined views

    421

    2 Sources, first seen 6h ago

    Combined views

    421

    2 Sources, first seen 6h ago

    9 likes
    6h ago
    first seen 6h ago
    9 likes
    4 comments
    8 reposts
    4 comments
    8 reposts

    2 Sources

    Sid Ravikumar@sidravi_Anyone renting RTX GPUs? I’m trying to understand the use cases for which people are renting lots of RTX GPUs such as RTX PRO 6000, 5090, 4090, etc. I am building an off-grid modular compute unit that hosts 2 RTX PRO 6000s per node. I have lots of offers from marketplace/aggregator platforms for renting them. But I would really love to understand end users and their use cases and workflows. The ideal use case for the compute I am building: - Does not need more than 96GB VRAM per GPU - Does not need high bandwidth clustering with NVLink and Infiniband - Does not need super high bandwidth or super low latency internet I am trying to understand scalable use cases for which people rent these consumer/workstation grade GPUs as opposed to clusters of B300/H200. Some examples would be: - Batch/flex tier inference on smaller LLMs (30-70B) - Inference for diffusion models - Training small robotics models with simulation environments that need RTX GPUs - Fine tuning - Domain specific models (incl for biotech, pharma, materials) - Rendering heavy workloads with agents in the loop Please post comments if you have insights or dm me if you can make some intros. If you fit in the above categories, I would love to chat and lunch/coffee is on me!6h
    Danielle Fong 🔆@DanielleFongRT @sidravi_: Anyone renting RTX GPUs? I’m trying to understand the use cases for which people are renting lots of RTX GPUs such as RTX PR…1h
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    2 Sources

    Sid Ravikumar@sidravi_Anyone renting RTX GPUs? I’m trying to understand the use cases for which people are renting lots of RTX GPUs such as RTX PRO 6000, 5090, 4090, etc. I am building an off-grid modular compute unit that hosts 2 RTX PRO 6000s per node. I have lots of offers from marketplace/aggregator platforms for renting them. But I would really love to understand end users and their use cases and workflows. The ideal use case for the compute I am building: - Does not need more than 96GB VRAM per GPU - Does not need high bandwidth clustering with NVLink and Infiniband - Does not need super high bandwidth or super low latency internet I am trying to understand scalable use cases for which people rent these consumer/workstation grade GPUs as opposed to clusters of B300/H200. Some examples would be: - Batch/flex tier inference on smaller LLMs (30-70B) - Inference for diffusion models - Training small robotics models with simulation environments that need RTX GPUs - Fine tuning - Domain specific models (incl for biotech, pharma, materials) - Rendering heavy workloads with agents in the loop Please post comments if you have insights or dm me if you can make some intros. If you fit in the above categories, I would love to chat and lunch/coffee is on me!6h
    Danielle Fong 🔆@DanielleFongRT @sidravi_: Anyone renting RTX GPUs? I’m trying to understand the use cases for which people are renting lots of RTX GPUs such as RTX PR…1h
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