E2B vs Miosa

Sandbox Benchmark Comparison · Updated October 30, 2026

Miosa was faster in both shared sandbox benchmarks.

Head to head

  • Burst TTITime to interactive · lower is better
    Miosa faster19.0x
    E2B
    1.27s
    Miosa
    67ms
  • DAXTotal workload time · lower is better
    Miosa faster1.86x
    E2B
    75.86s
    Miosa
    40.70s

Burst TTI

October 30, 2026

E2B

100% success
Median
1.27s
p95
1.47s
p99
1.70s
E2B Burst TTI results

Miosa

100% success
Median
67ms
p95
74ms
p99
75ms
Miosa Burst TTI results

Median time to interactive over time

12 runs · August 28, 2026 to October 30, 2026
E2BMiosa

E2B

100% success · October 30, 2026
Median
75.86s
E2B DAX results

Miosa

100% success · October 23, 2026
Median
40.70s
Miosa DAX results

Median total workload time over time

6 runs · August 21, 2026 to October 2, 2026
E2BMiosa
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Methodology

  • One workload, every provider. The same script, payload, and model hit every provider, addressed the way its own API expects. Nobody gets a tuned or special path.
  • Repeated on a schedule. Every suite runs many iterations per provider, automated on a recurring schedule, so results reflect steady state rather than one lucky request.
  • Raw results published. Every run is committed as JSON to the public benchmarks repo, next to the code that produced it. Nothing is cherry-picked or held back.
  • How this comparison is built. Each benchmark compares the two providers' medians; results within 5% count as roughly even. A comparison is published only when both providers completed at least 50% of runs in 2 or more shared benchmarks run in the last 30 days. If a provider’s latest run of a benchmark failed, its most recent successful run from that window is used instead.

Frequently asked questions

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Miosa was faster in both shared sandbox benchmarks. In Burst TTI (October 30, 2026), Miosa had a median time to interactive of 67ms versus 1.27s for E2B, 19.0x faster. In DAX (October 23, 2026), Miosa had a median total workload time of 40.70s versus 75.86s for E2B, 1.86x faster.

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