Cerebrium

Cerebrium is a serverless AI infrastructure platform that lets teams deploy Python code — from single functions to complex apps and pipelines — onto GPU instances with autoscaling, per-second billing, and cold starts measured in seconds (or milliseconds for warm pools). You write a cerebrium.toml and a Python entrypoint, run cerebrium deploy, and get an HTTPS endpoint (REST or streaming) backed by the GPU class you asked for — anything from CPU-only through T4, A10, L4, L40S, A100, and H100/H200. Cerebrium has invested heavily in the real-time voice-AI stack: WebSocket support, low-latency audio pipelines, and reference architectures combining Whisper/Distil-Whisper STT, an LLM, and ElevenLabs or Cartesia TTS with sub-second turn latency. Persistent volumes, secrets, cron jobs, batch jobs, and multi-region deployment round out the platform. Pricing is usage-based with a free tier ($30 credit), Standard, and Enterprise tiers featuring dedicated capacity, SOC 2, HIPAA, and BYOC. For teams building latency-sensitive AI products — voice agents, real-time image generation, custom inference stacks — who want less DevOps than raw Kubernetes but more control than a hosted model API, Cerebrium is a well-scoped middle ground.