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Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.
Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.
A paid gateway to premium OpenAI models with free daily credits, positioned as a ChatGPT Pro alternative.
Unified pay-per-generation API for 500+ image, video and audio models like FLUX, Kling and Seedance at low cost.
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
- ✦MiniMax M-series LLMs (M3, 1M context, MSA)
- ✦Hailuo AI video generation
- ✦Speech and music generation models
- ✦MiniMax Code agentic coding tool
- ✦Consumer apps (Hailuo, Xingye)
- ✦Open API and Token Plan for developers
- ✦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
- ✦Access to premium OpenAI models
- ✦Daily free credits
- ✦Subscription and pay-as-you-go options
- ✦Model picker for thinking/pro models
- ✦Invite-based bonus credits
- ✦Single API for 500+ image, video and audio models
- ✦Pay-per-generation billing with no subscription
- ✦No charge on failed tasks
- ✦Workflows, agents and studio tools
- ✦MCP and CLI integrations, white-label option
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Coding and agentic tasks
- →AI video generation
- →Text-to-speech and music creation
- →Building on MiniMax model APIs
- →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
- →Use OpenAI Pro-tier models affordably
- →Solve complex reasoning problems
- →Occasional AI use on free daily credits
- →Building apps on top of many generative models via one API
- →Generating images, video and audio at scale
- →Cutting model API costs versus direct providers
- →Deploying white-label AI generation studios