Best Agent Sandboxes in 2026: Cold Start, Per-Second Pricing, and Network Policy Across E2B, Daytona, Modal, Cloudflare, and Vercel

Every agent that writes code needs somewhere to run it. That “somewhere” is now a product category with at least a dozen vendors, four incompatible billing models, and marketing pages that quote cold starts measured under conditions nobody publishes.

This comparison fixes the units. It covers the five platforms most teams shortlist — E2B , Daytona , Modal Sandboxes , Cloudflare Sandbox SDK , and Vercel Sandbox — along with Runloop , Fly.io Sprites , and Northflank where they change the answer.

Feature matrices for this category are mostly noise. Four properties change architecture, and everything else is a preference:

The vendor claims are not comparable to each other. Daytona’s pricing page advertises sub-90ms sandbox creation . E2B is commonly cited at roughly 150ms. Modal advertises sub-second cold starts for pre-cached containers . None of these state concurrency, region, image size, or whether the clock stops at API acknowledgment or at first executed command.

The most useful public dataset is ComputeSDK’s sandbox leaderboard , which is open source and runs on a schedule. It measures Time to Interactive (TTI) : elapsed time from create() to the first successful command inside the sandbox, 100 iterations per provider, launched concurrently in a single burst, from a 4 vCPU host in Northern Virginia.

Three things in that table matter more than the ranking.

The task worth measuring is the one your agent runs, not echo hello . A useful harness runs the same unit of work everywhere: install pandas, read a CSV, plot it, return a PNG. Time four checkpoints separately.

Report tti and task separately. Vendors optimize the first and readers care about the second. Pin the region, pin the image, and publish both the sequential and the concurrent series, because they answer different questions.

Published rates as of August 27, 2026, converted to a common unit. Modal prices per physical core, which it defines as 2 vCPU, so the vCPU-equivalent is shown for comparison.

Rates are not costs. The model below fixes the workload and runs it through each rate card.

Assumptions: 2 vCPU / 4 GiB sandbox, 1,000 executions, no plan floor included, no egress, default region (Vercel iad1 , Cloudflare standard-3 at 2 vCPU / 8 GiB / 16 GB disk since instance sizes are fixed).

This is what a real agent loop looks like. The sandbox is open, the model is thinking, nothing is running.