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Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Affordable API platform for running image and video models like Nano Banana Pro (Gemini 3 Pro Image), priced pay-per-image.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
One API to access leading LLM, image, video, and audio models with pay-as-you-go, usage-based pricing.
- ✦LPU custom inference hardware
- ✦GroqCloud tokens-as-a-service API
- ✦High-speed, low-latency inference
- ✦Pay-as-you-go token pricing
- ✦Free API key to start
- ✦Broad open-model support
- ✦On-demand GPU pods across 30+ GPU types and 31 regions
- ✦Serverless GPU endpoints with sub-200ms cold starts
- ✦Zero idle cost billing for inference workloads
- ✦Multi-node clusters for distributed training
- ✦Persistent network storage for full pipelines
- ✦Real-time logs, monitoring and autoscaling from 0 to hundreds of workers
- ✦Pay-as-you-go access to Nano Banana Pro API
- ✦1K/2K/4K image generation
- ✦Many models (Seedream, Grok, GPT, Gemini)
- ✦Playground for testing prompts
- ✦REST and SDK integration
- ✦Usage logs, analytics and quota monitoring
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- ✦Single API for LLM, image, video, and audio models
- ✦Access to GPT, Claude, Gemini, Seedance, and more
- ✦Usage-based, pay-as-you-go pricing
- ✦Model comparison and documented capabilities
- ✦Smart Router for model selection
- ✦99.9% uptime, no credit card to start
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Renting GPUs for model training and fine-tuning
- →Deploying low-latency real-time inference APIs
- →Running AI agents that need to scale instantly
- →Processing compute-heavy batch or distributed workloads
- →Adding AI image generation to apps
- →Integrating Nano Banana Pro at low cost
- →Batch and high-volume image pipelines
- →Prototyping across many AI models
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →Add multiple AI models to a product via one API
- →Switch between model providers without rewrites
- →Generate video, images, and audio programmatically
- →Build AI agents and workflows