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Lambda Labs GPU Pricing 2026: A100 & H100 Hourly and Monthly Costs

2026/03/16

Reviewed September 12, 2026: Lambda lists single-GPU A100 40GB at $1.99/hr and H100 PCIe at $3.29/hr, or $1,452.70 and $2,401.70 for 730 hours before tax. A100 SXM 80GB is $2.79 per GPU-hour in an eight-GPU instance: $22.32 per instance-hour, not a $2.79 single-GPU rental.

Lambda Labs GPU Pricing (September 2026)

Quick answer: in the September 12, 2026 snapshot, single-GPU A100 40GB is $1.99/hour, H100 PCIe is $3.29/hour, and H100 SXM is $4.29/hour. At 730 hours, that is $1,452.70, $2,401.70, or $3,131.70 before applicable tax—not a discounted monthly plan.

The illusion is that "Lambda A100 price" or "Lambda H100 price" refers to one interchangeable GPU. It does not: memory capacity, PCIe versus SXM, and GPU count change both the hardware and the published per-GPU rate.

Lambda's public instance page was reviewed on September 12, 2026; the rates below were unchanged from our July snapshot. Listed pricing does not confirm regional stock.

Lambda instancePublished price per GPU-hourConfiguration noteSnapshot
1x A100 SXM 40GB$1.99Single-GPU instanceSeptember 12, 2026
1x A100 PCIe 40GB$1.99Single-GPU instanceSeptember 12, 2026
8x A100 SXM 80GB$2.79Per GPU; the instance contains eight GPUsSeptember 12, 2026
1x H100 PCIe 80GB$3.29Single-GPU instanceSeptember 12, 2026
1x H100 SXM 80GB$4.29Single-GPU instanceSeptember 12, 2026

The A100 80GB rate must not be presented as a single-GPU instance price: the public table exposes it in an 8x A100 SXM configuration and labels the price per GPU-hour. Renting that configuration costs 8 × $2.79 = $22.32 per instance-hour.

For simple 730-hour planning:

Lambda exampleHourly basisApprox. 730-hour cost
1x A100 40GB$1.99/GPU-hr$1,452.70
8x A100 SXM 80GB$22.32/instance-hr$16,293.60 for the instance
1x H100 PCIe 80GB$3.29/GPU-hr$2,401.70
1x H100 SXM 80GB$4.29/GPU-hr$3,131.70

What This Page Does and Does Not Claim

This page is intentionally narrow:

  • it uses provider-published public pricing
  • it does not freeze RunPod or Vast.ai marketplace quotes as if they were list prices
  • it does not treat a hyperscaler whole-VM price as identical to a managed single-GPU listing
  • it does not invent a Lambda rate for a GPU SKU that is not clearly published on the page reviewed

That is the cleanest way to answer Lambda pricing questions without letting the page turn into a stale quote graveyard.

Why Lambda Is Easier to Quote Than a Marketplace

Lambda is useful in pricing comparisons because it publishes fixed public list prices for self-serve GPU instances. That is very different from a marketplace where individual hosts can expose different offers at different times.

When people compare Lambda with RunPod or Vast.ai, they often flatten unlike-for-unlike pricing models into a single table. That is where bad content starts.

Lambda vs Public AWS and Google Cloud References

The following September 12, 2026 references use different pricing models. AWS examples are for US East (N. Virginia), not a global rate:

ProviderPublished examplePriceWhat the number actually is
Lambda1x A100 40GB$1.99/hrFixed self-serve instance price
Lambda8x A100 SXM 80GB$2.79/GPU-hrPer-GPU rate inside an eight-GPU instance
AWSp4d.24xlarge A100 Capacity Block$1.475/hr per acceleratorReserved-capacity example
Lambda1x H100 PCIe 80GB$3.29/hrFixed self-serve instance price
Lambda1x H100 SXM 80GB$4.29/hrFixed self-serve instance price
AWSp5.4xlarge H100 Capacity Block$5.191/hr per acceleratorSeptember 2026 reserved-capacity example
Google CloudA2/A3 accelerator-optimized VMCheck calculator or consoleWhole-VM price varies by machine type, region, and provisioning model

Google Cloud prices A2 A100 and A3 High/Mega H100 configurations as accelerator-optimized VMs. Use the applicable machine shape, region, and provisioning model in its pricing table or calculator. This review does not establish one comparable fixed Google Cloud quote. For the cross-provider comparison, use the cloud GPU price index; for host-marketplace versus tier pricing, use Vast.ai vs RunPod.

Monthly Cost Examples Based on Published Rates

For the September 12, 2026 snapshot, multiply the published rate by planned hours. A 40-hour week on a single A100 40GB is $79.60; on a single H100 PCIe it is $131.60 before tax. At 730 hours per month:

Published exampleApprox. monthly cost
Lambda A100 40GB at $1.99/hr$1,452.70/mo
Lambda 8x A100 80GB at $22.32/instance-hr$16,293.60/mo for the instance
Lambda H100 PCIe at $3.29/hr$2,401.70/mo
Lambda H100 SXM at $4.29/hr$3,131.70/mo
AWS A100 Capacity Block example at $1.475/hr$1,076.75/mo
AWS H100 Capacity Block example at $5.191/hr$3,789.43/mo

These are arithmetic projections, not universal invoices or monthly reservations. Lambda notes that applicable tax can be added. The AWS A100 example is a per-accelerator allocation inside an eight-GPU instance; the whole p4d.24xlarge at $11.80/hour projects to $8,614 for 730 hours. AWS Capacity Blocks have their own purchasable durations and reservation terms, so a 730-hour multiplication is not an offered block quote.

Price History

SnapshotA100 40GBA100 80GBH100 PCIe 80GBH100 SXM 80GB
April 2026$1.99/hrNot recorded$3.29/hr$4.29/hr
July 30, 2026$1.99/hr$2.79/GPU-hr in 8x instance$3.29/hr$4.29/hr
September 12, 2026$1.99/hr$2.79/GPU-hr in 8x instance$3.29/hr$4.29/hr

Does Lambda Publicly List RTX 4090?

The public Lambda pricing page reviewed for this update is centered on data-center GPU pricing. If your actual job is an RTX 4090-class workload, do not force a Lambda comparison where it does not belong.

Instead:

Bottom Line

Lambda is one of the cleanest public baselines for self-serve A100 and H100 pricing because it publishes simple fixed hourly rates.

If you need:

  • a clear public self-serve number, Lambda is useful
  • a hyperscaler reference, use Google Cloud VM pricing or AWS Capacity Block examples and label them carefully
  • a live marketplace rate, verify it in the deployment flow on RunPod or the live market on Vast.ai instead of copying an old blog quote

Related guides:


Official sources reviewed September 12, 2026:

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SynpixCloud Team

SynpixCloud Team