You're paying AWS prices for GPUs.

There's a better way.

You're paying AWS prices

for GPU Compute.

There's a better way.

We ran the same workloads side by side. The numbers speak for

themselves, and we're not hiding the ones where AWS wins either.

The numbers speak for themselves, and we're not hiding the ones where AWS wins either.

The Solidus AI Tech

Advantage

  • GPU pricing. Consistently 30–40% cheaper on every hardware tier we offer.

  • Developer simplicity. No IAM rabbit holes, no VPC setup. Run a job in 4 minutes from signup.

  • Provisioning speed. No quota bureaucracy. Jobs start in under 60 seconds.

  • Consumer GPU access. RTX 6000s to H200s — accessible for all, not just companies.

GPU Hourly Pricing Comparison

On-demand rates. No hidden fees. no support tier taxes.

H200

$2.4/hr

$4.5/hr

$4.7/hr

H100

$2.3/hr

$4.1/hr

$4.2/hr

A100

$1.7/hr

$3.2/hr

$3.3/hr

RTX 6000

$0.9/hr

$2.3/hr

$2.4/hr

Run Cost Simulation

Estimate monthly infrastructure spend across hyperscalers versus Solidus.

Hyperscaler Est.
$38,000
Solidus Est.
$25,000
Cost Advantage
Monthly Delta
$13,000
Savings
34.2%
Update the pricing values inside the script to match your live rates.

Common questions.

Especially from people coming from AWS

How is this so much cheaper than AWS?

We focus exclusively on compute — no S3, no Lambda, no RDS. That focus lets us optimize procurement, infrastructure, and pricing without cross-subsidizing a 200-product cloud ecosystem. We also work with a network of data centers, giving us supply flexibility AWS doesn't have.

How hard is it to migrate from AWS?

If your workload is just GPU compute — training, inference, batch processing — migration is usually a single afternoon. Our CLI is compatible with most standard PyTorch/TF workflows. If you're deeply integrated into AWS services (S3, SageMaker Pipelines), there's more work but we have a migration guide.

What's the reliability like? Can I trust this for production?

We maintain 99.9% uptime SLA across our GPU fleet. For pure training and batch inference workloads, this is more than sufficient. For latency-sensitive, customer-facing inference with strict SLAs, we'd encourage testing thoroughly before full migration.

Do you offer reserved or committed pricing?

Yes — monthly commit pricing gets you an additional 20% discount on top of our already-lower base rates. No multi-year lock-in required. Talk to us if you're spending $10K+/month and we'll build a custom plan.

Run your first job.

See the difference yourself

No credit card required to configure your machine. Takes 3 minutes.

Powering the next generation of autonoumous systems with unified Infrastructure.

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