Cerebrium: Serverless AI Infrastructure for Real-time Applications

Cerebrium

3.5 | 237 | 0
Type:
Website
Last Updated:
2025/09/22
Description:
Cerebrium is a serverless AI infrastructure platform simplifying the deployment of real-time AI applications with low latency, zero DevOps, and per-second billing. Deploy LLMs and vision models globally.
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serverless GPU
AI deployment
real-time AI
LLM deployment

Overview of Cerebrium

Cerebrium: Serverless AI Infrastructure for Real-Time Applications

What is Cerebrium? Cerebrium is a serverless cloud infrastructure platform designed to simplify the building and deployment of AI applications. It offers scalable and performant solutions for running serverless GPUs with low cold starts, supports a wide range of GPU types, and enables large-scale batch jobs and real-time applications.

How Does Cerebrium Work?

Cerebrium simplifies the AI development workflow by addressing key challenges in configuration, development, deployment, and observability:

  • Configuration: It provides easy configuration options, allowing users to set up new applications within seconds. The platform avoids complex syntax, enabling quick project initialization, hardware selection, and deployment.
  • Development: Cerebrium helps streamline the development process, providing tools and features that reduce complexity.
  • Deployment: The platform ensures fast cold starts (averaging 2 seconds or less) and seamless scalability, allowing applications to scale from zero to thousands of containers automatically.
  • Observability: Cerebrium supports comprehensive tracking of application performance with unified metrics, traces, and logs via OpenTelemetry.

Key Features and Benefits

  • Fast Cold Starts: Applications start in an average of 2 seconds or less.
  • Multi-Region Deployments: Deploy applications globally for better compliance and improved performance.
  • Seamless Scaling: Automatically scale applications from zero to thousands of containers.
  • Batching: Combine requests into batches to minimize GPU idle time and improve throughput.
  • Concurrency: Dynamically scale applications to handle thousands of simultaneous requests.
  • Asynchronous Jobs: Enqueue workloads and run them in the background for training tasks.
  • Distributed Storage: Persist model weights, logs, and artifacts across deployments without external setup.
  • Wide Range of GPU Types: Choose from T4, A10, A100, H100, Trainium, Inferentia, and other GPUs.
  • WebSocket Endpoints: Enable real-time interactions and low-latency responses.
  • Streaming Endpoints: Push tokens or chunks to clients as they are generated.
  • REST API Endpoints: Expose code as REST API endpoints with automatic scaling and built-in reliability.
  • Bring Your Own Runtime: Use custom Dockerfiles or runtimes for complete control over application environments.
  • CI/CD & Gradual Rollouts: Support CI/CD pipelines and safe, gradual rollouts for zero-downtime updates.
  • Secrets Management: Securely store and manage secrets via the dashboard.

Trusted Software Layer

Cerebrium provides a trusted software layer with features like:

  • Batching: Combine requests into batches, minimizing GPU idle time and improving throughput.
  • Concurrency: Dynamically scale apps to handle thousands of simultaneous requests.
  • Asynchronous jobs: Enqueue workloads and run them in the background - perfect for any training task
  • Distributed storage: Persist model weights, logs, and artifacts across your deployment with no external setup.
  • Multi-region deployments: Deploy globally by in multiple regions and give users fast, local access, wherever they are.
  • OpenTelemetry: Track app performance end-to-end with unified metrics, traces, and log observability.
  • 12+ GPU types: Select from T4, A10, A100, H100, Trainium, Inferentia, and other GPUs for specific use cases
  • WebSocket endpoints: Real-time interactions and low-latency responses make for for better user experiences
  • Streaming endpoints: Native streaming endpoints push tokens or chunks to clients as they’re generated.
  • REST API endpoints: Expose code as REST API endpoints - automatic scaling and improved reliability built-in.

Use Cases

Cerebrium is suitable for:

  • LLMs: Deploy and scale large language models.
  • Agents: Build and deploy AI agents.
  • Vision Models: Deploy vision models for various applications.
  • Video Processing: Scaled human-like AI experiences.
  • Generative AI: Breaking language barriers with Lelapa AI.
  • Digital avatars: Scaling digital humans for Virtual assistants with bitHuman

Who is Cerebrium For?

Cerebrium is designed for startups and enterprises looking to scale their AI applications without the complexities of DevOps. It is particularly useful for those working with LLMs, AI agents, and vision models.

Pricing

Cerebrium offers a pay-only-for-what-you-use pricing model. Users can estimate their monthly costs based on compute requirements, hardware selection (CPU only, L4, L40s, A10, T4, A100 (80GB), A100 (40GB), H100, H200 GPUs, etc.), and memory requirements.

Why is Cerebrium Important?

Cerebrium simplifies the deployment and scaling of AI applications, enabling developers to focus on building innovative solutions. Its serverless infrastructure, wide range of GPU options, and comprehensive features make it a valuable tool for anyone working with AI.

In conclusion, Cerebrium is a serverless AI infrastructure platform that offers a comprehensive set of features for deploying and scaling real-time AI applications. With its easy configuration, seamless scaling, and trusted software layer, Cerebrium simplifies the AI development workflow and enables businesses to focus on innovation. The platform supports various GPU types, asynchronous jobs, distributed storage, and multi-region deployments, making it suitable for a wide range of AI applications and use cases.

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