benchmark-models

Run the same prompt across Claude, GPT, and Gemini to benchmark gstack skills.

12|6|Updated Dec 2, 2025

Search Tags:#models #ai #comparison #latency #benchmark #cost #gstack

Ready to run

npx skills add https://github.com/shogo-labs/shogo-ai --skill benchmark-models-shogo-labs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: benchmark-models
Source: https://github.com/shogo-labs/shogo-ai/tree/main/packages/agent-runtime/templates/virtual-engineering-team/.shogo/skills/gstack-benchmark-models
Command: npx skills add https://github.com/shogo-labs/shogo-ai --skill benchmark-models-shogo-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a standardized way to compare AI model performance when applying gstack skills, by running the same prompts across Claude, GPT, and Gemini and surfacing latency, token usage, and cost data.

Core Features & Use Cases

Cross-model prompt evaluation for gstack skills to identify the most effective model for a given task.
Latency, tokens, and cost comparison across providers, enabling data-driven model selection.
Use Case: Benchmark a new skill to decide which model delivers the best balance of speed and quality in your workflow.

Quick Start

Run the gstack-model-benchmark tool to start a cross-model comparison on a chosen prompt.

Frequently Asked Questions about benchmark-models

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I compare AI model performance for the same prompt?▼

To compare AI model performance, you can benchmark cross-model prompts across Claude, GPT, and Gemini to measure latency, token usage, and cost data for data-driven model selection.

What is the best way to evaluate latency and cost across different AI models?▼

Evaluating latency and cost across different AI models involves running standardized benchmarking sessions that record token usage and response times, helping you identify the most effective model for your workflow.

How do I benchmark a new skill to choose the right AI model?▼

To benchmark a new skill, you run the same prompt across multiple providers like Claude, GPT, and Gemini, which records results to local analytics for comparison and helps decide the best balance of speed and quality.

Can I measure token usage and output quality across Claude, GPT, and Gemini?▼

Yes, you can measure token usage and output quality across Claude, GPT, and Gemini by running interactive prompts through a benchmarking tool that surfaces latency, token counts, and cost data.

Do I need specific frontmatter to identify my skill for AI model benchmarking?▼

Yes, the benchmarking process reads the SKILL.md frontmatter to identify the skill, locates the necessary benchmark binary, and runs interactive prompts to collect input for cross-model comparison.

What are the limitations of using standardized prompts for cross-model AI comparison?▼

Standardized cross-model AI comparison relies on running the exact same prompt across providers, meaning it may not account for model-specific prompt optimization techniques or vary input complexity across different test sessions.