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Deploy When Available is now GA
Queue for any GPU spec, even one that's fully rented out, and we'll deploy it the moment capacity opens up. No more refreshing the console or running a sniping tool.
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Join Runpod CEO Zhen Lu and Data Science Dojo CEO Raja Iqbal on October 11 for a live fireside chat about GPU-powered AI transformation and the future of.

Join us for an engaging fireside chat with Runpod on the cutting-edge GPU solutions that are revolutionizing the ML landscape and driving seamless AI transformation. Runpod and Data Science Dojo are excited to collaborate in this fireside chat and provide insights into the cutting-edge GPU solutions reshaping the ML landscape and driving seamless AI transformation.

This is an exciting time for large language models, with Llama-2 finetunes dominating the open source LLM landscape and the scope of 100b+ models continuing to grow. The required compute to harness these models also continues to grow as a natural result, which leads to challenges that require expertise and know-how to overcome.
During this event, you'll discover:
To register, please do so through LinkedIn here.
See you there!
Author profile: Brendan McKeag
Blog Posts
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Queue for any GPU spec, even one that's fully rented out, and we'll deploy it the moment capacity opens up. No more refreshing the console or running a sniping tool.

Explore why faster chips have shifted the bottleneck to AI infrastructure, and what that means for teams running production workloads.
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With MIG, we can partition RTX 6000 Pro cards into isolated 24 GB instances. Here's when it makes sense for your workloads.