Best Agent Sandboxes in 2026: Cold Start, Per-Second Pricing, and Network Policy Across E2B, Daytona, Modal, Cloudflare, and Vercel
Agent sandbox platforms (E2B, Daytona, Modal, Cloudflare, Vercel, Runloop, Fly.io, Northflank) are a rapidly maturing product category with at least a dozen vendors and four incompatible billing models Cold start performance varies dramatically: Daytona leads at 0.27s median TTI but only achieves 37% success under concurrent burst; Vercel leads at 0.67s median with 100% reliability Four properties fundamentally determine architecture: cold start under concurrency, filesystem persistence between
Analysis
TL;DR
- Agent sandbox platforms (E2B, Daytona, Modal, Cloudflare, Vercel, Runloop, Fly.io, Northflank) are a rapidly maturing product category with at least a dozen vendors and four incompatible billing models
- Cold start performance varies dramatically: Daytona leads at 0.27s median TTI but only achieves 37% success under concurrent burst; Vercel leads at 0.67s median with 100% reliability
- Four properties fundamentally determine architecture: cold start under concurrency, filesystem persistence between turns, egress policy, and idle billing
- Vendor claims are incomparable because they omit concurrency, region, image size, and measurement methodology; independent benchmarks (ComputeSDK leaderboard) reveal the true picture
- Pricing models diverge significantly: some charge per active CPU only (Vercel, Cloudflare), others per allocated resources (Northflank), and Modal bills per physical core (2 vCPU)
Why It Matters
As agentic AI systems become mainstream, every code-writing agent requires an isolated execution environment, making sandbox selection a critical infrastructure decision that directly impacts latency, cost, and reliability. The lack of standardized benchmarks and incomparable vendor claims mean practitioners must independently validate performance under their own workloads rather than trusting marketing numbers.
Technical Details
- Cold Start Benchmarks (ComputeSDK, August 21 2026): Measured Time to Interactive (TTI) — elapsed from
create()to first successful command — across 100 concurrent iterations from a 4 vCPU host in Northern Virginia. Vercel Sandbox: 0.67s median / 1.04s P95 / 100% success. Modal: 0.88s / 1.00s P95 / 100%. Daytona: 0.27s median but only 37% success under burst (0.10s sequential median on prior runs). Cloudflare: 5.06s median — architecturally heavier, using container scheduling rather than pre-warmed Firecracker VMs. - Four Decisive Properties: (1) Cold start under concurrency — agents creating sandboxes per tool call pay this tax thousands of times daily; (2) Filesystem persistence between turns — whether
pip installfrom turn 1 survives to turn 2; (3) Egress policy — internet access control and mid-session mutability; (4) Idle billing — agents spend most wall-clock time waiting on model responses, and someone pays for those seconds. - Pricing Models (as of August 27, 2026): E2B and Daytona: $0.0504/vCPU-hr, $0.0162/GiB-hr, wall-clock per second. Modal: $0.1419/core-hr (~$0.071/vCPU-hr), bills max(requested, actual). Vercel: $0.128/vCPU-hr on active CPU only, split billing. Cloudflare: $0.072/vCPU-hr active only, $0.009/GiB-hr provisioned. Fly.io Sprites: sleep when idle. Northflank: $0.01667/vCPU-hr — the lowest listed rate, billed on allocated resources.
- Recommended Benchmarking Harness: Run a realistic workload (install pandas, read CSV, plot, return PNG) across four checkpoints:
t_create → t_ready → t_deps → t_result. Report TTI and total task time separately, pin region and image, and publish both sequential and concurrent series.
Industry Insight
- Tail latency matters more than median for UX: Runloop's P95 is 3.3x its median — designing against the median will cause frequent UX failures. Agent frameworks must implement robust retry logic regardless of platform choice.
- Beware of incomparable vendor claims: Marketing numbers omit concurrency, region, image size, and measurement endpoints. Teams should reproduce benchmarks with their own workload before committing to a platform.
- Billing model divergence creates cost traps: Platforms charging on "active CPU only" (Vercel, Cloudflare) can appear cheaper but penalize I/O-heavy workloads; "allocated resources" models (Northflank) charge for idle time. Agent architectures that keep sandboxes alive between turns can dramatically reduce per-call cost on per-second billing platforms.
Disclaimer: The above content is generated by AI and is for reference only.