---
schema: 1
type: video
title: 'Under 5 minutes to a deployed LLM endpoint — Audry Hsu, RunPod'
description: >-
  Two failed crypto mining rigs in a basement in 2022. The founders posted on
  Reddit offering the GPUs for free in exchange for feedback. That is the origin
  of RunPod, now at $120 million in annual recurring revenue with 500,000
  developers on the platform. The demo runs in under five minutes: pick a model
  from the Hub, configure a context window, deploy a serverless endpoint on
  H100s. First request queues for 41 seconds on cold start while the container
  initializes and the model downloads. Every request after that executes in
  about 1.5 seconds. You pay only while a worker is handling a request. Speaker
  info: - https://www.linkedin.com/in/audry-hsu/ --- Watch along with the
  corrected transcript, summary, timestamps and resources on this talk's
  official AIE page:
  https://ai.engineer/talks/ILdE7FaAjVA-under-5-minutes-to-a-deployed-llm-endpoint-audry-hsu-runpod
  Join our upcoming AI Engineer conferences (see https://ai.engineer landing
  page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs
  and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference
  returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS
  2026 in Sydney ---
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markdown: >-
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updated: '2026-10-24T09:46:38.245Z'
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# Under 5 minutes to a deployed LLM endpoint — Audry Hsu, RunPod

Two failed crypto mining rigs in a basement in 2022. The founders posted on Reddit offering the GPUs for free in exchange for feedback. That is the origin of RunPod, now at $120 million in annual recurring revenue with 500,000 developers on the platform. The demo runs in under five minutes: pick a model from the Hub, configure a context window, deploy a serverless endpoint on H100s. First request queues for 41 seconds on cold start while the container initializes and the model downloads. Every request after that executes in about 1.5 seconds. You pay only while a worker is handling a request. Speaker info: - https://www.linkedin.com/in/audry-hsu/ --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/ILdE7FaAjVA-under-5-minutes-to-a-deployed-llm-endpoint-audry-hsu-runpod Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

Canonical: https://liquidgold.cc/channel/aidotengineer/explore/video/under-5-minutes-to-a-deployed-llm-endpoint-audry-hs-fd517b6916e5 · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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