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Use Case

Compute-heavy tasks.

Run compute-heavy workloads like rendering, simulations, and batch processing on powerful, on-demand GPUs.
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"Setup process was great—very quick and easy. RunPod had the exact GPUs we needed for inference and the pricing was very fair."
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Setup process was great—very quick and easy. RunPod had the exact GPUs we needed for inference and the pricing was very fair.
Read case study
Setup process was great—very quick and easy. RunPod had the exact GPUs we needed for inference and the pricing was very fair.
Read case study
Setup process was great—very quick and easy. RunPod had the exact GPUs we needed for inference and the pricing was very fair.
Read case study
"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."
Read case study
Setup process was great—very quick and easy. RunPod had the exact GPUs we needed for inference and the pricing was very fair.
Read case study

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.

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.
Templates

Find your next build.

Explore hundreds of official and community-built templates, ready to deploy in seconds.

Train large-scale LLMs and diffusion models.

Leverage PyTorch 2.1 on RunPod to fine-tune LLaMA 3, SDXL, or custom transformer models.

Fine-tune and generate AI art with Stable Diffusion.

Train custom Stable Diffusion models for photorealistic images, anime, or concept art.

Serve a high-performance AI chatbot at scale.

Deploy OpenAI-compatible models like Mistral and Mixtral for real-time conversational AI.

Deploy a real-time multimodal AI assistant.

Run large-scale language and vision models like LLaVA or OpenFlamingo with ultra-fast API serving.
Browse hundreds more
Developer Tools

Built-in developer tools & integrations.

Powerful APIs, CLI, and integrations
that fit right into your workflow.
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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 what’s next.

The most cost-effective platform for building, training, and scaling machine learning
models—ready when you are.

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