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All-in-one digital-safety subscription protecting families from identity theft, fraud and online threats, with parental controls.
Cloud platform from the makers of PyTorch Lightning for building, training and deploying AI in browser-based GPU Studios.
AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
Developer platform for fast serverless inference and training of open generative models, billed per token or GPU-second.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Free trial available
No public pricing
- ✦Identity theft protection with insurance
- ✦3-bureau credit monitoring and lock
- ✦Antivirus, VPN and password manager
- ✦Online data removal from brokers
- ✦Parental controls and safe-gaming alerts
- ✦Dark-web and financial-fraud alerts
- ✦Browser-based Lightning Studios with on-demand GPUs
- ✦PyTorch Lightning training framework
- ✦Model training, fine-tuning and deployment
- ✦Collaborative, shareable ML environments
- ✦Scalable multi-GPU/multi-node compute
- ✦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%
- ✦Serverless per-token inference with OpenAI/Anthropic-compatible APIs
- ✦On-demand dedicated and reserved GPU deployments
- ✦Fine-tuning and reinforcement-learning training pipelines
- ✦Large library of open LLM, vision, image and audio models
- ✦Optimized inference engine for throughput and latency
- ✦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
- →Protecting against identity theft
- →Monitoring family credit and finances
- →Keeping kids safe online
- →Removing personal data from broker sites
- →Prototype and train ML models in the cloud
- →Fine-tune and deploy foundation models
- →Run reproducible AI experiments collaboratively
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Serving open models in production apps and agents
- →Fine-tuning models on private data
- →Powering code assistants, chatbots and RAG at scale
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API