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Single API and playground for 1000+ AI models (chat, image, video, audio) with pay-as-you-go billing.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.
General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.
Free trial available
No public pricing
- ✦One API for 1000+ models
- ✦OpenAI/Anthropic-compatible endpoints
- ✦Chat, image, video, audio and embedding models
- ✦AI playground/sandbox
- ✦Pay-as-you-go billing across models
- ✦Enterprise dedicated infrastructure option
- ✦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
- ✦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
- ✦One unified, OpenAI-compatible API for 400+ models
- ✦Automatic provider failover for higher uptime
- ✦Edge routing for low latency
- ✦Custom data and provider policies
- ✦Pay-as-you-go credits usable across any model
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- →Integrating many AI models via one API
- →Prototyping and scaling AI apps
- →Cost-controlled multi-model access
- →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
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Accessing many LLMs through one integration
- →Adding provider redundancy to AI apps
- →Comparing model price and performance
- →Powering agents and AI-native products
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent