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The largest peer-to-peer GPU rental marketplace: 17,000+ GPUs from 1,400+ hosts in 500+ locations, per-second billing, typically 50-80% cheaper than AWS or GCP.

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Vast.ai is the largest peer-to-peer GPU rental marketplace, an Airbnb for GPUs operating since 2018. It aggregates 17,000+ GPUs from 1,400+ independent hosts across 500+ locations and clears 700,000+ rental transactions per month, typically at 50-80% below AWS or GCP list prices. Three product lines cover the spread: GPU Cloud for on-demand instances in 40+ data centers, Serverless for autoscaling model endpoints, and Clusters for multi-node InfiniBand training.

Key Features

  • Marketplace pricing across 68+ GPU types: from a GTX 1080 around $0.04/hr up to a B300 around $7.21/hr; RTX 4090 roughly $0.34-0.67/hr, A100 $0.66-1.50/hr, H100 SXM $2.36-3.35/hr.
  • Per-second billing: $5 minimum credit, no contracts; interruptible spot instances run 30-60% cheaper.
  • Serverless endpoints: autoscaling model serving billed per compute-second, scaling to zero when idle.
  • Clusters: multi-node InfiniBand fabric for large training runs.
  • Docker-first workflow: launch containers with SSH or Jupyter access, driven by the vastai CLI, Python SDK, or REST API.
  • Trust and compliance tiers: Verified Datacenter, Verified, and Community host tiers; SOC 2 certified, with a Secure Cloud filter for ISO 27001 vetted providers.

Use Cases

Who Should Use This Tool?

  • AI/ML researchers: training and fine-tuning runs that would blow a cloud budget.
  • Indie developers and small studios: inference, rendering, and batch jobs on consumer-grade cards.
  • Teams with bursty workloads: serverless endpoints that scale to zero between requests.

Problems It Solves

  1. Cloud GPU sticker shock: marketplace pricing typically lands 50-80% under AWS/GCP.
  2. Quota friction: 68+ GPU types available on demand without enterprise contracts.
  3. Paying for idle time: per-second billing and spot instances fit short, bursty jobs.

Pricing

GPU (typical range) Price per hour
GTX 1080 ~$0.04
RTX 4090 ~$0.34-0.67
A100 ~$0.66-1.50
H100 SXM ~$2.36-3.35
B300 ~$7.21

Marketplace prices move with supply and demand. Unverified Community hosts can push effective costs 20-40% higher through downtime, so the cheapest listed price is not always the cheapest completed job.

Advantages & Unique Selling Points

Compared to Competitors:

  1. Versus AWS/GCP: typically 50-80% cheaper for equivalent hardware.
  2. Versus single-provider clouds: unmatched breadth, from GTX 1080 to B300.
  3. Versus reserved capacity: per-second billing, spot discounts, and scale-to-zero serverless.

What Makes It Stand Out:

  • Scale: 17,000+ GPUs, 1,400+ hosts, 700,000+ rentals a month.
  • Host reliability tiers plus SOC 2 and ISO 27001 filtering for compliance-sensitive work.

Getting Started

Quick Start Guide

  1. Create an account: add as little as $5 in credit.
  2. Filter offers: search by GPU type, price, and reliability tier.
  3. Launch: pick a Docker template with SSH or Jupyter access.
  4. Automate: use the vastai CLI, Python SDK, or REST API for scripted workflows.

Integration

  • Docker images with SSH or Jupyter front ends.
  • vastai CLI, Python SDK, and REST API.
  • Secure Cloud filter for ISO 27001 vetted datacenter providers.

Frequently Asked Questions

Is Vast.ai reliable?

It depends on the tier you pick. Verified Datacenter and Verified hosts carry reliability guarantees; unverified Community hosts are cheaper but risk downtime.

What is the cheapest way to run?

Interruptible spot instances, which price 30-60% below on-demand.

Is it compliant enough for company use?

Vast.ai is SOC 2 certified, and the Secure Cloud filter restricts offers to ISO 27001 vetted providers.

Are there contracts or minimums?

No contracts. Billing is per second with a $5 minimum credit.

Alternatives

  • Modal: serverless Python-native compute with per-second GPU billing.
  • E2B: sandboxed code execution for agents rather than raw GPU rental.
  • Daytona: persistent dev environments with computer use.

Tips & Best Practices

  1. Match tier to stakes: production inference belongs on Verified Datacenter hosts; experiments can ride Community offers.
  2. Use spot for fault-tolerant training: checkpoint often and take the 30-60% discount.
  3. Model effective cost, not sticker cost: a cheap unverified host that kills your job mid-run costs more than a stable one.

Conclusion

Vast.ai remains the default answer when the question is "where do I get a GPU without a cloud contract": unmatched inventory breadth, per-second billing, and prices that routinely undercut the hyperscalers by half or more. Pick the right reliability tier, and it is the most cost-effective GPU capacity on the open market.

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