Published: March 13, 2025
Author: Matt Yantzer
Read Time: 3 Minutes

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Who Uses GPU Trader—And What They’re Building

We started GPU Trader with a simple belief: you shouldn’t need a million-dollar cloud budget to fine tune a model, inferenceing or launch a new AI idea. What’s happened since has exceeded anything we imagined. Today, our platform is experiencing curiosity from people in biotech, law, education, media, and more. Below are just a few of the folks we expect to build big things with flexible GPU access—no red tape, no massive infra team required.

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User Profiles

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1. The Biotech Researcher

  • Profile: PhD student at a university in Switzerland
  • Need: A100s for protein-folding models on a tight deadline
  • Built: A novel compound discovery model used in a preclinical study

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2. The Indie ML Engineer

  • Profile: Solo developer building an AI assistant for legal document review
  • Need: Experience with RTX 3090s, but now needd access to H100s for fine-tuning a custom LLM
  • Built: A GPT-based legal contract summarizer now piloting with firms in LA

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3. The Educator

  • Profile: Professor running a generative AI class at a state university
  • Need: A batch of A6000 GPUs for a one-week final project sprint
  • Built: A classroom-wide deployment simulation that prepped students for real-world ML ops

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4. The AI Artist

  • Profile: Creative technologist building video stories with open-source models
  • Need: High-VRAM GPUs for long-form frame generation
  • Built: An award-nominated short film powered entirely by AI tools

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Patterns We’re Seeing

Across all these users, we’re noticing trends:
  • Builds are faster when GPU access is frictionless
  • Demos beat decks: people want to show, not just tell
  • Startups scale smarter when GPU cost matches stage, not aspiration
If you’re building something new, GPU Trader exists to help you skip the waitlists, budget approvals, and cloud guesswork, and just get to work.