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Compare GPU and LLM inference API pricing between Beam and Google Cloud. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Beam Price | Google Cloud Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
Tesla T4 16GB VRAM • Google Cloud | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | Not Available | — | ||
Tesla V100 32GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | Not Available | — | ||
Tesla V100 32GB VRAM • | ||||
Explore how these providers compare to other popular GPU cloud services
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Only charged when your code runs, no charges for cold starts or server spin-up
Ultrafast boot times with advanced container optimization
Run untrusted code safely in isolated environments for AI agents and code interpreters
Pause and resume sessions while maintaining filesystem, memory, and running processes
Scale to zero when idle, burst to thousands of containers in seconds
Bring your own Docker images for full environment control
Scalable virtual machines with a wide range of machine types, including GPUs.
Managed Kubernetes service for deploying and managing containerized applications.
Event-driven serverless compute platform.
Fully managed serverless platform for containerized applications.
Unified ML platform for building, deploying, and managing ML models.
Short-lived compute instances at a significant discount, suitable for fault-tolerant workloads.
Deploy high-performance inference endpoints with custom models
Secure code execution environments for AI agents
Run large-scale workloads with distributed processing
Offers customizable virtual machines running in Google's data centers.
Managed Kubernetes service for running containerized applications.
Serverless compute platform for running code in response to events.
Only pay for actual compute time with no minimum charges
Developer plan free with usage, Team plan starts at monthly base fee plus usage
All plans include monthly free credits for getting started
Pay for compute capacity per hour or per second, with no long-term commitments.
Automatic discounts for running instances for a significant portion of the month.
Save up to 57% with a 1-year or 3-year commitment to a minimum level of resource usage.
Save up to 80% for fault-tolerant workloads that can be interrupted.
Sign up on the Beam platform
Create a virtual environment and install the Beam SDK
Configure your API token to connect to Beam
Set up a project in the Google Cloud Console.
Set up a billing account to pay for resource usage.
Select Compute Engine, GKE, Cloud Functions, or Cloud Run based on your needs.
Launch a VM instance, configure a Kubernetes cluster, or deploy a function/application.
Use the Cloud Console, command-line tools, or APIs to manage your resources.
40+ regions and 120+ zones worldwide.
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.