Aigregator Logo
Aigregator
Cerebrium logo

Cerebrium

Serverless GPU infrastructure platform for deploying real-time AI workloads.

Last updated: Jul 21, 2026

Pricing

Updated: Jul 2, 2025
Starting Price
Contact for pricing
Pricing Model
usage-based
Free Plan
No
Free Trial
No

About Cerebrium

Cerebrium is a serverless AI infrastructure platform designed for teams to build, deploy, and scale multimodal AI applications with minimal operational complexity. It specializes in delivering sub-second cold starts and instant autoscaling for voice agents, video models, LLMs, and other AI workloads across distributed GPU and CPU resources. The platform eliminates traditional infrastructure management overhead by allowing developers to bring their own code or Dockerfile without requiring rewrites or custom SDKs. The platform is particularly distinguished by its low-latency performance—achieving 2-4 second cold starts—and instant access to thousands of GPUs across multiple clouds and regions without reservations or lock-ins. Cerebrium provides comprehensive observability through native OpenTelemetry support, SOC 2 Type II compliance, and HIPAA-ready security standards. A key limitation is that it requires users to understand containerization and deployment workflows, which may present a learning curve for teams without infrastructure expertise.

At a glance

Company
Cerebrium (est. 2022)
Platforms
Web, API
API
Available
Integrations
OpenTelemetry, Twilio, LiveKit
Last verified
July 2026
Last updated: July 21, 2026

Who It's For

  • •Engineering teams building AI applications
  • •Companies deploying voice and video AI models
  • •Enterprises requiring regulated, compliant infrastructure
  • •Developers seeking low-latency AI inference
  • •Teams managing real-time AI workloads at scale

How It Works

  1. 1Developers upload their code or Dockerfile to Cerebrium
  2. 2The platform creates memory and GPU snapshots for fast container restores
  3. 3Cerebrium automatically scales workloads in real time based on demand
  4. 4Each workload runs in a hardened, isolated gVisor container environment
  5. 5Multi-region failover ensures 99.999% uptime with automatic traffic routing
  6. 6Full observability is provided through logs, metrics, and scaling events

How to Use Cerebrium

  1. 1Sign up on the Cerebrium platform and obtain API credentials
  2. 2Point the platform to your application entry point or Dockerfile
  3. 3Deploy without code rewrites—Cerebrium runs your application as-is
  4. 4Monitor performance through the dashboard with real-time logs and metrics
  5. 5Leverage OpenTelemetry integration to connect existing monitoring stacks
  6. 6Optionally specify data residency regions for regulatory compliance

Key Features

  • •Sub-second cold starts with memory and GPU snapshotting
  • •Instant autoscaling without capacity planning
  • •Multi-region deployment across US, EU, and Asia-Pacific
  • •Pay-per-second pricing with no reservations or lock-ins
  • •SOC 2 Type II, HIPAA, GDPR, and ISO compliance
  • •Data residency controls for regulated workloads
  • •End-to-end observability with OpenTelemetry support
  • •gVisor container isolation for security
  • •Multi-region failover for 99.999% uptime
  • •Support for custom code without SDK requirements

Use Cases

  • •Deploying real-time voice agents with sub-500ms response latency
  • •Running large language models and generative AI applications in production
  • •Scaling video and image processing workloads automatically
  • •Building low-latency digital avatars and virtual assistants
  • •Transcribing and processing audio content at scale

Pros & Cons

Advantages

  • •Exceptional low-latency performance with 2-4 second cold starts, significantly faster than traditional Kubernetes-based solutions
  • •True serverless experience with automatic scaling and no infrastructure management, capacity planning, or lock-in contracts
  • •Enterprise-grade compliance and security with SOC 2 Type II, HIPAA, GDPR support and gVisor isolation
  • •Pay-per-second pricing model aligns costs directly with actual usage

Disadvantages

  • •Limited geographic coverage compared to major cloud providers, with only 4 regions mentioned
  • •Requires developer familiarity with containerization and Dockerfiles
  • •Early-stage platform (Y Combinator W22) may have less mature tooling compared to established cloud providers

Reviews for Cerebrium

0.0

Based on 0 reviews

Rating Distribution

No Reviews Yet

Be the first to share your experience with Cerebrium!

Frequently Asked Questions

What is Cerebrium?

Cerebrium is a serverless AI infrastructure platform designed for teams to build, deploy, and scale multimodal AI applications with minimal operational complexity. It specializes in delivering sub-second cold starts and instant autoscaling for voice agents, video models, LLMs, and other AI workloads across distributed GPU and CPU resources.

How much does Cerebrium cost?

Cerebrium uses custom pricing — contact the vendor for a quote.

Is Cerebrium free?

Cerebrium is a paid tool and does not offer a free plan.

What are the best Cerebrium alternatives?

Popular Cerebrium alternatives include Beam Cloud, Avian AI Inference Platform, Dify AI.

What is Cerebrium used for?

Cerebrium is commonly used for Deploying real-time voice agents with sub-500ms response latency, Running large language models and generative AI applications in production, Scaling video and image processing workloads automatically.

Does Cerebrium have an API?

Yes, Cerebrium offers an API for developers.

What platforms does Cerebrium support?

Cerebrium is available on Web, API.

Information Accuracy

Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.