Cerebrium
Cerebrium is a serverless AI infrastructure platform that enables businesses to build, deploy, and scale machine learning models quickly with sub-5 second cold-start times and 40% cost savings compared to traditional cloud providers.
https://www.cerebrium.ai?ref=aipure
Product Information
Updated:Feb 16, 2025
Cerebrium Monthly Traffic Trends
Cerebrium received 12.7k visits last month, demonstrating a Slight Decline of -15.4%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is Cerebrium
Founded in 2021 and part of Y Combinator W22 batch, Cerebrium is a platform that provides serverless GPU infrastructure for machine learning applications. It serves as an AWS Sagemaker alternative, offering a comprehensive solution for developers and businesses to deploy AI models in the cloud efficiently and at scale. The platform supports all major ML frameworks and allows users to deploy both pre-built models and custom solutions through their API.
Key Features of Cerebrium
Cerebrium is a serverless GPU infrastructure platform designed for machine learning that enables developers to build, deploy, and monitor AI models with minimal engineering overhead. It offers sub-5 second cold-start times, supports multiple GPU types, and provides cost savings of up to 40% compared to traditional cloud providers like AWS and GCP. The platform includes comprehensive observability tools, automated scaling, and integrates with major ML frameworks while maintaining high security standards.
Serverless GPU Infrastructure: Access to 8+ different GPU types including H100, A100, and A5000, with sub-5 second cold start times and automatic scaling capabilities
Comprehensive Monitoring & Logging: Real-time logging, monitoring with alerts, and performance profiling tools to track application health and performance
Cost-Efficient Operations: Pay-as-you-go pricing model with typical cost savings of 40% compared to traditional cloud providers, along with detailed cost management tools
Enterprise-Grade Security: SOC 2 and HIPAA compliant platform with 99.999% uptime guarantee and robust security features
Use Cases of Cerebrium
AI Model Deployment: Deploy machine learning models at scale with support for all major frameworks and ability to chain together LLMs and custom models
Real-time Video Processing: Handle tasks such as object tracking, video analysis, and speech transcription with optimal resource allocation
Educational AI Applications: Build and deploy voice-driven AI tutors and educational tools with low-latency requirements
Large Language Model Inference: Process large language models efficiently with optimized inference engines and cost-effective token processing
Pros
Significant cost savings compared to traditional cloud providers
Fast cold start times under 5 seconds
Comprehensive monitoring and observability tools
Enterprise-grade security compliance
Cons
Relatively new platform (founded in 2021)
Limited track record compared to established cloud providers
How to Use Cerebrium
Install and Initialize Cerebrium: Install Cerebrium and create a template project using the command 'cerebrium init'. This will create a folder with all necessary files to get started.
Configure cerebrium.toml: Set up your environment and hardware configurations in the cerebrium.toml file that was created during initialization. Here you can specify GPU types, scaling parameters, deployment config, and build parameters.
Add Secrets: Navigate to the Cerebrium dashboard and add any required authentication tokens or secrets (like Hugging Face tokens) under the 'Secrets' section. These can be accessed in your code using get_secret().
Write Your Code: Add your Python code for the AI model. Code at the top level is instantiated only during container spin-up, while function code runs on each call.
Deploy Your Model: Deploy your model to Cerebrium using their deployment commands. After deployment, you can monitor it through the Cerebrium dashboard.
Monitor and Scale: Use the Cerebrium dashboard to monitor your deployment's performance, view real-time logs, track costs, and observe scaling behavior. The platform automatically handles scaling based on demand.
Optimize and Iterate: Use Cerebrium's observability tools to monitor performance and costs. Adjust your configurations and code as needed to optimize for better performance or cost efficiency.
Cerebrium FAQs
Cerebrium is a serverless GPU infrastructure provider that helps run machine learning models in the cloud efficiently and at scale. It allows users to build, test and deploy AI applications quickly with cost savings of 40%+ compared to AWS or GCP.
Official Posts
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Analytics of Cerebrium Website
Cerebrium Traffic & Rankings
12.7K
Monthly Visits
#1660563
Global Rank
#19733
Category Rank
Traffic Trends: Oct 2024-Jan 2025
Cerebrium User Insights
00:01:58
Avg. Visit Duration
3.09
Pages Per Visit
45.61%
User Bounce Rate
Top Regions of Cerebrium
US: 26.24%
IN: 13.06%
DE: 9.71%
VN: 7.88%
CA: 7.3%
Others: 35.81%
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