Together AI and Y Combinator partner to launch the first dedicated GPU cluster for the YC community

Together AI Blog ·

A partnership announcement between Together AI and Y Combinator describing a dedicated GPU cluster for YC portfolio startups, citing compute as a key bottleneck, outlining a short-term sprint access model with long-term pricing, and detailing self-service GPU provisioning via Together’s portal with dedicated billing support. Read 4 viewpoints with supporting evidence and source links.

Deveaux Barron, Ankit Gupta, Ellie O'Neil

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4 key points

Synthesis

  1. First dedicated YC GPU cluster launched

    Together AI and Y Combinator announced a partnership to deliver the first dedicated GPU cluster for YC's portfolio of AI-native startups, enabling easier access to compute for building and scaling.

    Supporting evidence 1

    Original excerpt

    Today, Together AI and Y Combinator (YC) are announcing a partnership to deliver the first dedicated YC GPU cluster, giving YC's portfolio of AI-native startups easier access to the compute they need to build and scale.

    Deveaux Barron, Ankit Gupta, Ellie O'Neil · Paragraph 3

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  2. Compute is the biggest bottleneck

    Compute has become the biggest bottleneck for AI-native startups.

    Supporting evidence 1

    Original excerpt

    Compute has become the biggest bottleneck

    Deveaux Barron, Ankit Gupta, Ellie O'Neil · Paragraph 4

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    compute constraints →
  3. Short-term GPU sprints with long-term rates

    YC portfolio startups can spin up GPUs for short-term sprints while benefiting from long-term pricing—avoiding long-term commitments.

    Supporting evidence 1

    Original excerpt

    Instead of long-term commitments, startups can spin up GPUs for short-term sprints while benefiting from long-term rates.

    Deveaux Barron, Ankit Gupta, Ellie O'Neil · Paragraph 9

    Context

    Together AI and Y Combinator have partnered to solve that specific problem. Together AI has built a dedicated cluster and developer experience just for YC Portfolio companies to quickly and cost-effectively get access to compute for their AI needs across inference and training.

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    GPU access model →
  4. Founders self-provision GPUs via portal

    Startups reserve, provision, and manage their own GPUs directly through Together’s self-service portal, with dedicated billing support. GPU provisioning takes minutes, and startups have full usage control from day one.

    Supporting evidence 1

    Original excerpt

    Startups reserve, provision, and manage their own GPUs directly through Together’s self-service portal, with their own billing support, so scaling compute never has to route through YC. Founders get GPUs ready in minutes, and stay in control of their own usage from day one.

    Deveaux Barron, Ankit Gupta, Ellie O'Neil · Paragraph 11

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Key passages4

Attributed passages with the context to verify them. Open the original text to check the source.

GPU access model

Short-term GPU sprints with long-term rates

Original excerpt

Instead of long-term commitments, startups can spin up GPUs for short-term sprints while benefiting from long-term rates.
Context

Together AI and Y Combinator have partnered to solve that specific problem. Together AI has built a dedicated cluster and developer experience just for YC Portfolio companies to quickly and cost-effectively get access to compute for their AI needs across inference and training.

self-service infrastructure

Founders self-provision GPUs via portal

Original excerpt

Startups reserve, provision, and manage their own GPUs directly through Together’s self-service portal, with their own billing support, so scaling compute never has to route through YC. Founders get GPUs ready in minutes, and stay in control of their own usage from day one.

Source & methodology

These viewpoints are linked to their original sources. Paraphrases are labeled and are not verbatim quotes.

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