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Kimi is Moonshot AI's conversational assistant known for long-context chat, coding help, and agentic tasks.
Low-cost inference cloud with developer APIs to run open ML models and on-demand GPUs, billed pay-per-use.
AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
A paid gateway to premium OpenAI models with free daily credits, positioned as a ChatGPT Pro alternative.
AI research lab building multimodal 'omni' foundation models and infrastructure aimed at robotics and physical-world applications.
No public pricing
No public pricing
No public pricing
- ✦Conversational AI assistant
- ✦Long-context document understanding
- ✦Coding assistance
- ✦Agent and plugin capabilities
- ✦Web and mobile app access
- ✦Hosted inference for many open models
- ✦Simple REST/OpenAI-compatible API
- ✦Pay-per-token or per-time billing
- ✦On-demand GPU rental
- ✦Broad catalog (Llama, DeepSeek, Qwen, Flux, etc.)
- ✦DeepStart and DeepCluster tooling
- ✦NVIDIA GPU instances (H100, H200, B200, GB200)
- ✦On-demand and preemptible GPU pricing
- ✦High-performance and object storage
- ✦Managed Kubernetes and Slurm (Soperator)
- ✦Serverless and managed inference (Token Factory)
- ✦MLOps tooling and 24/7 expert support
- ✦Commitment discounts up to 35%
- ✦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
- ✦Omni multimodal model research and development
- ✦Real-time inference API (Infer) for enterprise use
- ✦Video tagging, search, and clipping infrastructure
- ✦Training data generation from egocentric and robotics footage
- →Answering questions and research
- →Summarizing long documents
- →Writing and editing help
- →Coding support
- →Serving open-source models via API
- →Building AI apps cost-efficiently
- →Renting GPUs for inference or training
- →Scaling inference up and down on demand
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Use OpenAI Pro-tier models affordably
- →Solve complex reasoning problems
- →Occasional AI use on free daily credits
- →Powering robotics perception with multimodal AI
- →Running large-scale video search and analysis via API
- →Sourcing specialized training data for frontier AI models