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Unified API to 500+ AI models (OpenAI, Anthropic, Google, etc.) with OpenAI-compatible calls priced ~20% below official rates.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Cloud platform to run open-source AI apps like ComfyUI and Stable Diffusion and train LoRAs on rented GPUs, billed hourly.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
Free trial available
Free trial available
- ✦One key for 500+ models
- ✦OpenAI-compatible API
- ✦Pay-as-you-go credits (~20% below list)
- ✦Multimodal: text, image, video, audio
- ✦Usage analytics and budget alerts
- ✦Integrations (Claude Code, n8n, Zapier, etc.)
- ✦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
- ✦Pre-installed open-source AI apps (ComfyUI, SD, Fooocus)
- ✦LoRA and custom model training
- ✦Image, video, audio, and LLM workflows
- ✦Hourly GPU rental across several tiers
- ✦Private storage and shareable workflows
- ✦No-deployment, browser-based access
- ✦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
- ✦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
- →Consolidating multi-provider AI billing
- →Switching models without re-integration
- →Powering apps and automation pipelines
- →Benchmarking models in one playground
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Running ComfyUI/Stable Diffusion without a local GPU
- →Training custom LoRA models
- →Face swapping and voice conversion
- →Generating images, video, and audio at scale
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →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