The cheapest GPU cloud

The cheapest GPU cloud

Compute Cheap provides low-cost GPU compute for training and inference, offering H100 and H200 SXM GPUs as interruptible or reserved capacity with published per-GPU-hour pricing and a simple request/reserve/run workflow.

The cheapest GPU cloud is ai agents software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Freemium API Enterprise 75/100
#512 in AI Agents (512 tools)
Just launched
Data reviewed Sep 5, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: AI Agents

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Freemium from $1.15 per GPU-hour (updated Sep 4, 2026)

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The cheapest GPU cloud

Compute Cheap positions itself as a provider of very low-cost GPU compute for training and inference, explicitly offering NVIDIA H100 SXM 80GB and H200 SXM 141GB capacity. It publishes per-GPU-hour prices for interruptible and reserved capacity (for example, H100 interruptible listed at $1.15 per GPU-hour, updated Sep 4, 2026) and advertises being "the world's cheapest GPU compute." The product targets teams running frontier models by providing limited reserved and interruptible capacity in launch sizes from 1 to 8 GPUs, with a minimum reservation of 2,000 GPU-hours and a three-step flow: request capacity, confirm availability with a 50% upfront prepayment, then run workloads.

Affordable H100 and H200 GPU compute for training, inference, and everything in between.

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Key Features

H100 & H200 GPU options

Offers H100 SXM 80GB and H200 SXM 141GB GPUs for training and inference, listed as available in launch sizes from 1 to 8 GPUs.

Interruptible and Reserved capacity

Two capacity types: interruptible (lower cost, can be reclaimed) and reserved (fixed rate for the full block).

Published per-GPU-hour pricing

Shows explicit hourly rates such as H100 interruptible $1.15/hr, H100 reserved $1.19/hr, H200 interruptible $1.39/hr, and H200 reserved $1.99/hr.

Block reservation workflow

Three-step process: request capacity, confirm availability and prepay 50% to reserve the block, then run workloads against the reserved GPUs.

Minimum reservation

Minimum reservation is 2,000 GPU-hours per request.

Market benchmarking chart

Interactive chart to compare the provider's price against daily market benchmarks across a 31-day window.

Pricing

H100 Interruptible

$1.15 per GPU-hour (updated Sep 4, 2026)
  • Lower-cost but interruptible (can be reclaimed)
  • Launch sizes 1–8 GPUs

H100 Reserved

$1.19 per GPU-hour
  • Fixed rate for the reserved block
  • Minimum reservation 2,000 GPU-hours

H200 Interruptible

$1.39 per GPU-hour
  • Lower-cost but interruptible

H200 Reserved

$1.99 per GPU-hour
  • Fixed reserved rate

Use Cases

Training frontier models

Provision H100/H200 capacity for multi-GPU training runs; the product emphasizes usage by teams training frontier models.

Inference and serving

Run inference and serving workloads on H100/H200 GPUs as part of production or research pipelines.

Fault-tolerant or batch training

Use interruptible capacity for cheaper batch or fault-tolerant training jobs that can tolerate preemption.

Integrations

No verified integration details are available.

Benefits

Low published GPU-hour pricing compared to market benchmarks (explicit H100 and H200 rates shown).
Flexibility between lower-cost interruptible capacity and guaranteed reserved blocks.
Clear reservation workflow with availability confirmation and prepaid deposit to secure capacity.
Support for multi-GPU launch sizes (1–8 GPUs) suitable for scaling training runs.

Limitations

Capacity is limited and offered in launch sizes of 1–8 GPUs; availability must be confirmed before payment.
Minimum reservation is relatively large (2,000 GPU-hours).
Interruptible capacity can be reclaimed during demand spikes and is therefore not suitable for non-fault-tolerant workloads.
Some GPU types (e.g., NVIDIA GB300 and B200) are marked as sold out / currently unavailable.

Frequently Asked Questions

What's the difference between reserved and interruptible capacity?
Reserved capacity stays yours for the full block, at a fixed rate. Interruptible capacity costs less per GPU-hour but can be reclaimed if demand spikes, so it suits fault-tolerant training and batch jobs.
Is there a minimum reservation?
Yes, 2,000 GPU-hours per request. That's roughly 8 GPUs for 10 days, or fewer GPUs over a longer window, split however your workload needs.
How does the 50% deposit work?
Compute Cheap confirms availability for your exact request before you pay anything. Once confirmed, you prepay 50% of the block upfront to reserve it, and the remaining 50% is billed as usage completes.
What happens if the capacity I asked for isn't available?
They only take a deposit after availability is confirmed, so you're never charged for a block they can't deliver. If exact availability is tight, they'll offer the closest match before you commit.
Which GPUs can I request?
H100 SXM 80GB and H200 SXM 141GB, in launch sizes from 1 to 8 GPUs. Additional hardware comes online as capacity is secured.
How is the price calculated?
Hourly rate × GPU-hours, shown before you request. There's no separate platform fee layered on top of the GPU-hour price.

Getting Started

  1. 1 Step 1: Request capacity — choose H100 or H200, select interruptible or reserved, and specify GPU-hours (minimum 2,000 GPU-hours).
  2. 2 Step 2: Confirm availability — Compute Cheap confirms availability for your exact request and you prepay 50% upfront to reserve the block.
  3. 3 Step 3: Run your workload — use the reserved GPUs to train, serve, and scale; remaining 50% is billed as usage completes.

Support

email

Contact support via [email protected] (address shown in site footer).

contact page

Site includes a 'Contact' link in the header for additional inquiries.

docs / blog

Blog and pricing posts linked on the site provide pricing history and infrastructure explanations.

API

Available: Yes

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