Cerebrium

Cerebrium provides serverless infrastructure for real-time AI applications, enabling developers to deploy LLMs, agents, and vision models globally with low latency and zero DevOps overhead. The platform offers per-second billing, automatic scaling from zero to thousands of containers, and supports 12+ GPU types including T4, A10, A100, H100, and H200. Trusted by companies like Deepgram, Vapi, Tavus, and LiveKit, Cerebrium simplifies the entire development workflow from configuration to observability.

• Fast Cold Starts - Average app starts in 2 seconds or less, ensuring minimal latency for real-time applications
• Auto-scaling - Scale from zero to thousands of requests automatically and only pay for compute you actually use
• Multi-region Deployments - Deploy globally across multiple regions for better compliance and improved performance for users worldwide
• 12+ GPU Types - Select from T4, L4, A10, A100, L40s, H100, H200, Trainium, Inferentia, and other GPUs for specific use cases
• WebSocket & Streaming Endpoints - Native support for real-time interactions, low-latency responses, and streaming tokens as they're generated
• Batching & Concurrency - Combine requests into batches to minimize GPU idle time and dynamically scale to handle thousands of simultaneous requests
• Distributed Storage - Persist model weights, logs, and artifacts across deployments with no external setup required
• OpenTelemetry Integration - Track app performance end-to-end with unified metrics, traces, and log observability
• Bring Your Own Runtime - Use custom Dockerfiles or runtimes for absolute control over app environments
• CI/CD & Gradual Rollouts - Support for CI/CD pipelines and safe, gradual rollouts for zero-downtime updates
• Secrets Management - Store and manage secrets securely via the dashboard to keep API keys hidden and safe
• SOC 2 & HIPAA Compliance - Enterprise-grade security ensuring data is secure, available, and private

To get started, sign up for a free account with $30 in free credits (no credit card required), initialize a project, choose your desired hardware, and deploy. The platform handles scaling, infrastructure management, and observability automatically.