Pydantic vs VercelAI Gateway Benchmark Comparison

Pydantic
Faster in 2 of 2
vs
Vercel
Faster in 0 of 2

Pydantic was faster in both shared AI gateway benchmarks.

Shared benchmarks
2
Last run
October 30, 2026
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Scorecard

Median of each benchmark's primary metric; lower is better. Medians within 5% count as roughly even, and a benchmark gets no speed verdict when either provider completed fewer than 50% of runs.

BenchmarkPydanticVercelResultRatio
Anthropic
Cold end-to-end latency · Run October 30, 2026
393ms
100% success
495ms
100% success
Pydantic faster
1.26x
OpenAI
Cold end-to-end latency · Run October 30, 2026
681ms
100% success
735ms
100% success
Pydantic faster
1.08x

Anthropic

Run October 30, 2026

Time for a cold request routed through the gateway to Claude Haiku 4.5 to return its complete response.

Cold end-to-end latency

Pydantic

100% success
Median
393ms
P95
475ms
P99
514ms
Pydantic Anthropic results →

Vercel

100% success
Median
495ms
P95
820ms
P99
869ms
Vercel Anthropic results →

Pydantic had a 1.26x lower median cold end-to-end latency (393ms vs 495ms for Vercel).

Median cold end-to-end latency over time

15 runs from July 24, 2026 to October 30, 2026.

PydanticVercel
View the full Anthropic leaderboard →

OpenAI

Run October 30, 2026

Time for a cold request routed through the gateway to GPT-5.4 Mini to return its complete response.

Cold end-to-end latency

Pydantic

100% success
Median
681ms
P95
962ms
P99
1063ms
Pydantic OpenAI results →

Vercel

100% success
Median
735ms
P95
1088ms
P99
1159ms
Vercel OpenAI results →

Pydantic had a 1.08x lower median cold end-to-end latency (681ms vs 735ms for Vercel).

Median cold end-to-end latency over time

11 runs from August 21, 2026 to October 30, 2026.

PydanticVercel
View the full OpenAI leaderboard →

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 the latency benchmark on at least two of the same model families reliably: at least 50% success for each provider, in benchmark runs from the last 30 days.

Frequently asked questions

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Pydantic was faster in both shared AI gateway benchmarks. In Anthropic (October 30, 2026), Pydantic had a median cold end-to-end latency of 393ms versus 495ms for Vercel, 1.26x faster. In OpenAI (October 30, 2026), Pydantic had a median cold end-to-end latency of 681ms versus 735ms for Vercel, 1.08x faster.

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