What is Cerebrium?

Cerebrium is a serverless AI infrastructure platform that supports rapid deployment of large language models, vision models, and agent-based applications. It offers zero DevOps management, auto‑scaling from zero to thousands of containers, and per‑second billing for efficient cost control.

The service provides fast cold starts (≤2 seconds), multi‑region deployment, and native WebSocket and streaming endpoints for low‑latency real‑time interactions. Users can select from more than 12 GPU types—including T4, A10, A100, H100, Trainium, and Inferentia—directly from the dashboard, and can customize runtime environments with Dockerfiles or native runtimes.

Integrated OpenTelemetry, batching, concurrency, asynchronous job queues, and distributed storage simplify observability, throughput, and data persistence without external setup. The platform supports CI/CD pipelines, gradual rollouts, and secure secrets management, making it suitable for developers, ML engineers, and enterprises that require reliable, compliant AI deployment at scale.

Cerebrium pricing Freemium

Hobby $0/mo

Standard $100/mo

Enterprise custom

Verify on the official pricing page.

View plans

Cerebrium user reviews

Based on 3 reviews, 66.7% of users recommend Cerebrium, rated highly for quality results.

recommend

don't

3 reviews

Liked for

Quality results 2 of 2

Worth the price 2 of 2

Easy to use 1 of 2

All key features 1 of 2

Disliked for

Inconsistent results 1 of 1

Missing features 1 of 1

Would you recommend Cerebrium?

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Cerebrium's key features

Serverless AI deployment platform
Global multi-region deployment
Per-second usage billing
Auto-scaling to thousands containers
GPU request batching
Distributed storage for models
Real-time WebSocket and streaming endpoints

Cerebrium use cases

Deploy a real‑time image‑captioning microservice for e‑commerce product feeds using Cerebrium's serverless vision models, auto‑scaling GPUs, and low‑latency WebSocket endpoints—no DevOps or infrastructure maintenance required.
Launch a multi‑region chatbot for a global SaaS platform, leveraging Cerebrium's zero‑DevOps LLM deployment, per‑second billing, and containerized GPU selection to keep response latency under 50 ms while scaling automatically during peak usage.
Implement an event‑driven document‑analysis pipeline that runs language models on user uploads, automatically spinning up GPU containers on demand and billing by the second—streamlining compliance checks without provisioning servers.