benchmark-models

To compare AI model performance, you can run identical prompts across Claude, GPT, and Gemini to measure latency, token usage, and cost side-by-side. This benchmarking approach surfaces the metrics needed to inform model selection.

The best way to benchmark LLM providers is prompt-readiness testing, which executes the same prompt across multiple authenticated providers. It captures token usage and output quality to evaluate which model best balances speed and cost for customer-facing features.

Yes, you need authenticated access for the providers you want to test. The benchmarking process automatically manages authentication status, checking which providers are available and including only those authenticated models in the run.

Yes, you can evaluate GPT via Codex CLI against Claude and Gemini. The benchmark runs the same prompt across these specific providers to compare latency, token usage, and cost, helping you decide which model best fits your use case.

Limitations include requiring access to the gstack-benchmark binary and authenticated providers for Claude, GPT, and Gemini. If a provider is not authenticated, it is automatically excluded from the benchmark run, limiting your comparison scope.