Announcing Runpod Flash

Compute-heavy tasks.

Run compute-heavy workloads like rendering, simulations, and batch processing on powerful, on-demand GPUs.

Trusted by top engineers at the world's leading companies.
How TOOL Scales Big AI Ideas on Runpod

"All of these projects, the renders for AMD, the Coca-Cola builds, that has to do with scalability. If we can't scale, we can't deliver. Runpod makes that possible."

How Aneta Handles Bursty GPU Workloads Without Overcommitting

"Runpod has changed the way we ship because we no longer have to wonder if we have access to GPUs. We've saved probably 90% on our infrastructure bill, mainly because we can use bursty compute whenever we need it."

How Gendo uses Runpod Serverless for Architectural Visualization

"Runpod has allowed the team to focus more on the features that are core to our product and that are within our skill set, rather than spending time focusing on infrastructure, which can sometimes be a bit of a distraction.”

How Civitai Trains 800K Monthly LoRAs in Production on Runpod

"Runpod helped us scale the part of our platform that drives creation. That’s what fuels the rest, image generation, sharing, remixing. It starts with training."

How Scatter Lab Powers 1,000+ Inference Requests per Second with Runpod

"Runpod allowed us to reliably handle scaling from zero to over 1,000 requests per second in our live application."

How InstaHeadshots Scales AI-Generated Portraits with Runpod

"Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all."

How KRNL AI scaled to 10K+ concurrent users while cutting infra costs 65%.

"We could stop worrying about infrastructure and go back to building. That’s the real win.”

How Coframe scaled to 100s of GPUs instantly to handle a viral Product Hunt launch.

“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”

How Glam Labs Powers Viral AI Video Effects with Runpod

"After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds."

How Segmind Scaled GenAI Workloads 10x Without Scaling Costs

Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity, without overpaying for idle resources.

High-performance compute, on demand.

Harness the power of Runpod's GPUs for intensive, parallelized workloads.

GPU-powered speed

Leverage A100 and H100 GPUs for simulations and rendering.

Parallel processing

Run large-scale jobs even faster with high-efficiency multi-GPU execution.

Compute-heavy tasks
Compute-heavy tasks

Scale compute precisely when you need it.

Run massive compute workloads with dynamic scaling and zero idle costs.

Pay-per-use pricing

Avoid idle GPU costs and pay only for active inference time.

Spot GPU savings

Use low-cost spot instances to reduce expenses without sacrificing performance.

Deploy and run HPC jobs effortlessly.

Launch pre-configured environments for simulations, rendering, and AI training.

Pre-config setups

Launch environments with CUDA, PyTorch, and other dependencies ready to go.

Batch or interactive

Run large-scale batch jobs or interactive sessions—no manual config needed.

Compute-heavy tasks

Built-in developer tools & integrations.

Runpod SDK for programmatic API access: Python, JavaScript, and Go. Runpod CLI for resource management. Flash CLI for deployment and CI/CD integration. Deploy from your terminal, automate from your pipeline.

Full API access.

Automate everything with a simple, flexible API.

CLI & SDKs.

Deploy and manage directly from your terminal.

GitHub & CI/CD.

Push to main, trigger builds, and deploy in seconds.

Build something new today