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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.
Single API and playground for 1000+ AI models (chat, image, video, audio) with pay-as-you-go billing.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
Free trial available
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
- ✦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
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- →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
- →Integrating many AI models via one API
- →Prototyping and scaling AI apps
- →Cost-controlled multi-model access
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD