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Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Credit-based AI coding agent that builds full applications from plain-language instructions, including backend, billing, and admin features.
General AI agent that executes multi-step tasks end to end — research, slides, design, browsing — instead of only answering questions.
Free trial available
No public pricing
Free trial available
No public 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
- ✦One-line API calls to run community and proprietary AI models
- ✦Support for image, video, speech, and LLM generation models
- ✦Fine-tuning and custom model deployment via Cog
- ✦Per-second usage billing on shared or dedicated hardware
- ✦Automatic scaling for high-traffic private models
- ✦Thousands of community-published models with production APIs
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Builds complete apps (auth, storage, payments, admin) from natural-language prompts
- ✦Runs on top of multiple frontier coding models
- ✦Retains full project context across sessions for incremental feature additions
- ✦Remote task submission via Slack/Telegram messaging
- ✦'Eco Mode' for lower-cost usage without consuming credits
- ✦VS Code and JetBrains IDE integrations plus a desktop app
- ✦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
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Developers embedding image/video/speech generation into an app via API
- →Teams deploying and scaling their own fine-tuned models
- →Builders comparing outputs from multiple AI models in one playground
- →Companies avoiding GPU infrastructure management for ML inference
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Solo founders building a launchable product without a dev team
- →Developers offloading multi-step feature builds to an autonomous agent
- →Teams wanting a shared coding agent with pooled usage billing
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent