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Agent Arena

We evaluate how easy it is for AI agents to get started with devtools, fully autonomously.

Model: Claude Opus 4.6
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1Daytona
2m 21s
$0.81
0.8
1
2E2B
1m 18s
$0.84
1.6
2
3Modal
2m 46s
$1.16
1.3
1
4Freestyle
3m 39s
$1.20
1
1
5Vercel Sandbox
3m 18s
$2.20
2
1
6Blaxel
8m 44s
$3.50
1
1
7Cloudflare Sandbox
13m 11s
$4.73
2.7
0
8CodeSandboxblocks automated signup
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Methodology

An AI coding agent (Claude Opus 4.6) runs inside an isolated Docker container with a task prompt and a URL. The agent must autonomously discover docs, install packages, write working code, and verify the result — all without human help beyond providing API credentials when asked.

How rankings work: providers in the same category are ranked against each other on four dimensions — Time, Cost, Errors, and Interruptions. Within a category, the per-dimension rankings combine into an overall position. Less time, lower cost, fewer errors, and fewer interruptions all improve a provider's standing. No composite score, no letter grades.

All tool calls, errors, timing, and token usage are recorded. Rankings are deterministic from session logs. Multiple independent runs per provider are aggregated.

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