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AI Latency Benchmarks

Round-trip latencies from AWS Lambda to sandbox providers and LLM inference APIs.

Results

Sandbox Provider Latency

LLM Inference Latency

Methodology

  • Lambda: Node.js 20.x, 3072 MB, us-east-1 (Ashburn, VA)
  • Samples: 100 per test (10 fresh sandboxes x 10 samples each)
  • Sandbox tests: Coldstart = create() + delete(). Tool execution = echo ok via provider SDK. Network round trip = Sandbox Agent GET /v1/health.
  • LLM tests: Minimal prompt ("Hi", max_tokens=1) measuring network + inference overhead, not generation speed.
  • Sandbox provisioning and agent installation are excluded from exec/health measurements. Sandboxes are reused across samples within each iteration.

Network topology

ASN Location
Lambda AS14618 Amazon.com Ashburn, VA
E2B AS396982 Google LLC The Dalles, OR
Daytona AS30633 Leaseweb USA Centreville, VA

Usage

# Run all tests
./invoke.sh /run "tests=*&samples=5"

# CSV output
./invoke.sh /run "tests=llm:*&samples=10&format=csv"

# Full benchmark (10 iterations x 10 samples, outputs sandbox-raw.csv + provider-raw.csv)
./bench.sh

# Network info from Lambda
./invoke.sh /netinfo

# Deploy
./deploy.sh

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Lambda-based latency benchmarker for sandbox providers and LLM inference

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