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Dedicated Serverless GPU API endpoints

Runpod Serverless runs AI inference with sub-200ms FlashBoot cold starts, per-second billing, and scale to zero. Deploy any containerized model as an autoscaling GPU endpoint without managing servers.

Runpod Serverless endpoint interface illustration
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Bring your container.

Deploy any container with full control and flexibility.

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Network storage.

Persistent, high-speed storage that scales with your workloads.

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Global regions.

Deploy closer to your users with low-latency regions worldwide.

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What is Runpod Serverless?

Serverless GPU endpoints run containerized inference workloads behind an API and scale workers based on demand. Use Runpod Serverless when requests arrive in bursts, when you want to avoid idle compute, or when your team wants to deploy model inference without managing GPU servers.

Runpod Serverless at a glance

Updated July 2026

SpecRunpod Serverless
GPUs available13 tiers from 16GB to 280GB VRAM, including B300, B200, H200, H100, A100, RTX 6000 Pro, L40S, A6000, RTX 5090, RTX 4090, L4, and A4000
Cold startSub-200ms with FlashBoot; active workers stay pre-warmed for zero cold starts
Billing granularityPer second, from worker start to full stop, rounded up to the nearest second
AutoscalingScales from zero to hundreds of workers with request demand; flex workers scale to zero when idle
Price per hourFrom $0.58/hr (16GB class) to $9.98/hr (280GB B300), metered per second

From code to cloud.

Deploy, scale, and manage your entire stack
in one streamlined workflow.

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Effortlessly scale
AI inference.

When every element clicks, deploying, scaling, and optimizing becomes pure magic.

Flexible runtimes.

Run AI/ML workloads with support for a wide range of languages, frameworks, and custom configurations.

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Zero cold starts.

Pre-warmed functions guarantee an immediate response, eliminating all initial latency delays.

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<200ms cold-start with FlashBoot

Lightning-fast scaling with
sub-200ms cold-starts.

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Deploy with GitHub.

Push to GitHub, auto-release to your endpoint. Rollback anytime with ease.

What teams build with serverless.

See how teams are building AI apps, automation, and analytics—without managing infrastructure.

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Inference

Serve inference for image, text, and audio generation at any scale.

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Fine-tuning

Train custom models on
your specific datasets.

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Agents

Build intelligent agent-based systems and workflows.

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Compute-heavy tasks

Run compute-heavy workloads like rendering and simulations.

"The Runpod team has clearly prioritized the developer experience to create an elegant solution that enables individuals to rapidly develop custom AI apps or integrations while also paving the way for organizations to truly deliver on the promise of AI."

Amjad Masad

"Runpod is the only place I can deploy high-end GPU models instantly—no sales calls, no rate limits, no nonsense."

Daniel Chang

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

Josh Payne

“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.”

Matty Shimura

Serverless

Serverless GPU endpoints run containerized inference workloads behind an API and scale workers based on demand. Use Runpod Serverless for request-driven inference when your team wants to deploy models without managing GPU servers.

GPU

Workers
280
GB
B300

Maximum throughput for big models.

$
9.98
/hr
180
GB
B200

Maximum throughput for big models.

$
8.64
/hr
140
GB
H200

Extreme throughput for big models.

$
5.93
/hr
96
GB
RTX 6000 Pro
PRO

High throughput for large model inference workloads.

$
3.49
/hr
80
GB
H100
PRO

Extreme throughput for big models.

$
4.55
/hr
80
GB
A100

High throughput GPU, yet still very cost-effective.

$
2.72
/hr
48
GB
L40, L40S, 6000 Ada, MIG 48GB
PRO

Extreme inference throughput on LLMs like Llama 3 7B.

$
1.75
/hr
48
GB
A6000, A40

A cost-effective option for running big models.

$
1.22
/hr
32
GB
5090
PRO

Extreme throughput for small-to-medium models.

$
1.58
/hr
32
GB
RTX PRO 4500 Blackwell

Cost-effective Blackwell inference for 32GB workloads.

$
1.15
/hr
24
GB
4090
PRO

Extreme throughput for small-to-medium models.

$
1.10
/hr
24
GB
L4, A5000, 3090, MIG 24GB

Great for small-to-medium sized inference workloads.

$
0.69
/hr
16
GB
A4000, A4500, RTX 4000, RTX 2000

The most cost-effective for small models.

$
0.58
/hr
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Questions? Answers.

Serverless, simplified. Clear answers on running your code without the fuss.

Runpod’s serverless GPUs eliminate cold starts with always-on, pre-warmed instances, ensuring low-latency execution. Unlike traditional serverless solutions, Runpod offers full control over runtimes, persistent storage options, and direct access to powerful GPUs, making it ideal for AI/ML workloads.

Runpod supports Python, Node.js, Go, Rust, and C++, along with popular AI/ML frameworks like PyTorch, TensorFlow, JAX, and ONNX. You can also bring your own custom runtime via Docker containers, giving you full flexibility over your environment.

Runpod uses active worker pools and pre-warmed GPUs to minimize initialization time. Serverless instances remain ready to handle requests immediately, preventing the typical delays seen in traditional cloud function environments.

Runpod allows deployments directly from GitHub, with one-click launches for pre-configured templates. For rollback management, you can revert to previous container versions instantly, ensuring a seamless and controlled deployment process.

Runpod integrates with webhooks, APIs, and custom event triggers, enabling seamless execution of AI/ML workloads in response to external events. You can set up GPU-powered functions that automatically run on demand, scaling dynamically without persistent instance management.

Runpod offers a comprehensive monitoring dashboard with real-time logging and distributed tracing for your serverless functions. Additionally, you can integrate with popular APM tools for deeper performance insights and efficient debugging.

Trusted by today's leaders, built for tomorrow's pioneers.

Engineered for teams building the future.

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10,100,100,100

Requests since launch & 1M+ developers worldwide

Build what’s next.

Build, train, and scale AI workloads on Runpod with cloud GPUs, Serverless, and Clusters.

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