LLM API vs PydanticAI Gateway Benchmark Comparison
Pydantic was faster in both shared AI gateway benchmarks.
- Shared benchmarks
- 2
- Last run
- October 30, 2026
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.
Anthropic
Run October 30, 2026Time for a cold request routed through the gateway to Claude Haiku 4.5 to return its complete response.
Cold end-to-end latency
Pydantic had a 1.94x lower median cold end-to-end latency (393ms vs 762ms for LLM API).
Median cold end-to-end latency over time
10 runs from August 28, 2026 to October 30, 2026.
OpenAI
Run October 30, 2026Time for a cold request routed through the gateway to GPT-5.4 Mini to return its complete response.
Cold end-to-end latency
Pydantic had a 2.61x lower median cold end-to-end latency (681ms vs 1781ms for LLM API).
Median cold end-to-end latency over time
10 runs from August 28, 2026 to October 30, 2026.
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 762ms for LLM API, 1.94x faster. In OpenAI (October 30, 2026), Pydantic had a median cold end-to-end latency of 681ms versus 1781ms for LLM API, 2.61x faster.