.jpeg)
Deploy When Available is now GA
Queue for any GPU spec, even one that's fully rented out, and we'll deploy it the moment capacity opens up. No more refreshing the console or running a sniping tool.
Blog
Runpod has reduced prices by across Serverless and Secure Cloud GPUs, making high-performance AI compute more accessible for developers.

Runpod is dropping prices across our Serverless and Secure Cloud services. Why? Because we believe in giving you the firepower you need to build applications without breaking the bank.
Let's cut to the chase. Here's what's changing:
We've trimmed the fat on our Serverless pricing. Check it out:
| GPU Model | Flex Worker (Old → New /hr) | Active Worker (Old → New /hr) |
|---|---|---|
| 16GB | $0.72 → $0.58 | $0.43 → $0.40 |
| 24GB | $0.94 → $0.69 | $0.58 → $0.48 |
| 24GB PRO | $1.58 → $1.10 | $0.94 → $0.77 |
| 48GB | $1.73 → $1.22 | $1.04 → $0.85 |
| 48GB PRO | $2.48 → $1.90 | $1.48 → $1.33 |
| 80GB | $4.68 → $2.72 | $2.81 → $2.17 |
| 80GB PRO | $9.00 → $5.59 | $5.40 → $4.47 |
That's right, we've slashed prices by up to 40% on some models. Your AI workloads just got a whole lot more affordable.
For those of you running beefy workloads, our Secure Cloud pricing has also gotten a makeover:
| GPU Model | Old Price → New Price /hr |
|---|---|
| AMD MI300X Instinct 192GB | $4.89 → $3.99 |
| Nvidia H100 SXM5 Hopper 80GB | $4.69 → $3.99 |
| Nvidia H100 NVL Hopper 94GB | $4.39 → $3.69 |
| Nvidia H100 PCIe Hopper 80GB | $3.69 → $3.29 |
| Nvidia A100 SXM4 Ampere 80GB | $2.19 → $1.94 |
| Nvidia A100 PCIe Ampere 80GB | $1.89 → $1.69 |
| Nvidia L40S Ada Lovelace 48GB | $1.34 → $1.19 |
| Nvidia 6000 Ada Lovelace 48GB | $1.14 → $1.03 |
| Nvidia L40 Ada Lovelace 48GB | $1.14 → $0.99 |
| Nvidia 4090 Ada Lovelace 24GB | $0.74 → $0.69 |
We've trimmed Secure Cloud prices across the board, with some models seeing cuts of up to 18%.
Look, we get it. AI development is expensive. GPUs aren't cheap, nor is the infrastructure to run them at scale. But we believe that great ideas shouldn't be held back by budget constraints.
We've been fortunate to secure some serious funding recently. And instead of blowing it all on fancy office chairs or an in-house barista (tempting as that was), we chose to invest the savings in you.
By optimizing our pricing, we're not just cutting costs – we're reinvesting in the platform and community to provide you with a better overall experience.
What This Means for You
Want to dive deeper into the numbers? Check out our complete pricing page for a full breakdown of all our GPU options and to find the perfect fit for your project.
We're not just about affordable GPUs. We're about giving you the tools you need to push the boundaries of what's possible with AI. That means reliability, performance, and support you can count on.
Our team is constantly working on improvements to make your Runpod experience even better.
This is just the beginning. We have big plans for the future, and we can't wait to share them with you. Keep an eye on our blog and GitHub for upcoming features and improvements.
In the meantime, why not take our new pricing for a spin? Whether you're a seasoned AI veteran or just dipping your toes into the world of AI applications, there's never been a better time to run with Runpod.
Let's build the future together – for less.
Author profile: Pardeep Singh
Blog Posts
.jpeg)
Queue for any GPU spec, even one that's fully rented out, and we'll deploy it the moment capacity opens up. No more refreshing the console or running a sniping tool.

Explore why faster chips have shifted the bottleneck to AI infrastructure, and what that means for teams running production workloads.
.jpeg)
With MIG, we can partition RTX 6000 Pro cards into isolated 24 GB instances. Here's when it makes sense for your workloads.