Beam Cloud
Serverless Inference

Developers deploying generative AI, TTS, or voice agents who need instant serverless scaling and sub-second cold starts.
Cerebrium has engineered one of the most advanced serverless GPU platforms on the market, specifically targeting the “cold start” problem that plagues serverless AI. Traditional platforms can take minutes to load massive model weights into VRAM, but Cerebrium utilizes advanced memory-mapping techniques to achieve sub-second cold starts. This allows developers to deploy massive LLMs or vision models cost-effectively, paying only for the exact milliseconds of compute used.
Instead of restricting developers to a curated list of models, Cerebrium operates as a deployment infrastructure. Data scientists can package custom PyTorch, TensorFlow, or ONNX models and deploy them as scalable API endpoints with a few lines of Python code. This makes it an ideal platform for startups building proprietary, heavily fine-tuned models that cannot be hosted on standard OpenAI-compatible APIs.
Cerebrium is built for production engineering teams. It offers native integrations with enterprise data lakes and vector databases, allowing seamless data pipelines. With SOC 2 compliance and the ability to deploy within secure VPCs, it provides the agility of serverless compute while maintaining strict corporate data governance.
SOC 2 Compliant, private VPC available
Custom Integration. This provider requires their own specific SDKs or libraries to interact with the models. See official documentation.
import requests
headers = {
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json'
}
data = {
'model': 'your-chosen-model',
'prompt': 'Hello, world!'
}
response = requests.post('https://cerebrium.ai/v1/completions', headers=headers, json=data)| Website | Visit Official Site ↗ |
You are charged exclusively for the duration the GPU is actively processing your request. Excellent for bursty workloads.
Start building without a credit card. Perfect for prototyping and testing the API before scaling into production workloads.
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Cerebrium uses a per-second billing model. You pay only for what you use — no idle server costs.
Cerebrium has its own API. Check their documentation for integration guides.
Cerebrium supports LLM, Vision, Audio, Custom Python. Use the API to deploy custom models or use their pre-built endpoints.
Yes, Cerebrium offers a free tier so you can test the platform without a credit card.
Serverless Inference
AI Researchers, PyTorch Lightning Users, Collaborative Model Development
Distributed Computing, Ray workload scaling, LLM hosting