AI Code Execution & Sandbox Environments Software Pricing 2026
Compare pricing for 4 ai code execution & sandbox environments tools. Find the right software for your budget.
AI Code Execution & Sandbox Environments software pricing ranges from $0 to $250 per user/month in 2026. The typical cost is around $49/user/month across 4 popular tools. Top picks: Devbox (Jetify) ($5–$250/user/mo), Daytona ($0.00–$0.00/user/mo), Gitpod ($20–$20/user/mo), and 1 more. 1 of 4 tools offer free tiers for small teams or limited use.
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Devbox (Jetify)
$5–$250/per month
Daytona
$0.00–$0.00/s
Gitpod
$20–$20/month
E2B
Free–$150/MONo matches
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AI Code Execution & Sandbox Environments Pricing FAQ
01 What is an AI code execution sandbox?
An AI code execution sandbox is an isolated, ephemeral environment where LLM-generated or agent-driven code runs safely. Because models can produce arbitrary code, sandboxes (like E2B and Modal) provide secure, resource-limited containers or microVMs that prevent the code from touching your systems, with fast startup and clean teardown after each run.
02 How much do code execution sandboxes cost?
Pricing is usually based on compute time, billed per second or per sandbox-hour, plus memory and any persistent storage. Free or trial tiers exist for development; production usage scales with how many sandboxes you spin up and how long they run. Short-lived, frequently-created sandboxes can add up at high agent throughput.
03 Why do AI agents need sandboxes?
AI agents that write and run code, analyze data, or use computer tools can generate unsafe or buggy code. Sandboxes contain that risk, providing isolation, resource limits, and reproducibility. They also let agents install packages and run real programs without polluting or endangering your production environment.
04 What hidden costs come with code sandboxes?
Watch for per-second compute that accumulates when agents spawn many sandboxes, idle time before teardown, storage for persistent workspaces, and egress fees. High-frequency agent loops that create a sandbox per step are the most common cause of unexpected costs.