A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.
AI Infrastructure comparison
Pricing, pros, cons, and ideal use cases — side by side.
A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.
Isolated sandboxes where an AI agent can run the code it just wrote without touching anything you care about.
| Baseten | E2B | |
|---|---|---|
| Pricing | PaidUsage-based pricing tied to the compute your deployed models consume. | FreemiumHobby is free with $100 one-time usage credits, community support, sessions up to 1 hour, and 20 concurrent sandboxes; no credit card required. Pro is $150/month with customisable sandbox CPU and RAM, sessions up to 24 hours, and 100 concurrent sandboxes, expandable by purchase to 1,100. Enterprise is custom. Compute is billed per second on vCPU, RAM, and storage on top of the plan fee. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Teams deploying custom or fine-tuned modelsEnterprises needing dedicated, autoscaling model servingOrgs that want to avoid managing GPU infrastructure | Teams shipping code-interpreter or data-analysis agent featuresAI product companies that must isolate customer-triggered code executionPlatform engineers building internal agent runtimesAnyone letting an LLM run generated code against real data |
E2B is the lighter-weight option (Freemium), while Baseten sits higher on the pricing ladder (Paid). Baseten is built around teams deploying custom or fine-tuned models; E2B leans more toward teams shipping code-interpreter or data-analysis agent features. Shortlist the one whose strengths line up with your biggest constraint.
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