Compare LLM Performance on Riddles
Promptfoo example that compares OpenAI GPT-5.4, Anthropic Claude Sonnet 4.6, and Google Gemini 3.1 Pro Preview on riddle-solving tasks with cost, latency
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Why it matters
Evaluate and compare the performance of leading large language models (GPT, Claude, Gemini) on riddle-solving tasks. Gain insights into their cost, latency, and quality for informed decision-making.
Outcomes
What it gets done
Benchmark GPT-5.4, Claude Sonnet 4.6, and Gemini 3.1 Pro Preview.
Assess riddle-solving accuracy across different LLMs.
Analyze cost and latency metrics for each model.
Generate comparative quality assertions.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/pfoo-compare-gpt-vs-claude-vs-gemini | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Steps
Steps in the chain
Overview
Compare Gpt Vs Claude Vs Gemini
This promptfoo example runs a structured benchmark comparing OpenAI GPT-5.4, Anthropic Claude Sonnet 4.6, and Google Gemini 3.1 Pro Preview on riddle-solving tasks. It measures and compares cost, latency, and quality assertions across all three models. Use this when you want a template for building custom multi-model evaluations. It's a starting point when cost and latency trade-offs are as important as answer quality in your model selection process.
What it does
This promptfoo example provides a ready-to-run benchmark comparing OpenAI's GPT-5.4, Anthropic's Claude Sonnet 4.6, and Google's Gemini 3.1 Pro Preview on riddle-solving tasks. It evaluates each model against cost, latency, and quality assertions.
When to use - and when NOT to
Use this when you want a template for building your own multi-model evaluations. Do NOT use this if you need production-scale load testing or benchmarks for tasks other than riddle-solving - you'll need to adapt the test cases and assertions for your specific use case.
Inputs and outputs
You provide three API keys (OpenAI, Anthropic, and Google) as environment variables. The workflow runs a predefined set of riddle-solving prompts against all three models and outputs a comparative evaluation report showing cost, latency, and quality metrics for each model.
Integrations
This example integrates with:
- OpenAI API - Tests GPT-5.4 models
- Anthropic API - Tests Claude Sonnet 4.6 models
- Google AI API - Tests Gemini 3.1 Pro Preview models
- Promptfoo CLI - The evaluation framework that orchestrates the comparison
Who it's for
This example serves as both a working benchmark and a template you can fork to test models on your own prompts and assertions.
Getting started
Initialize the example and navigate to its directory:
npx promptfoo@latest init --example compare-gpt-vs-claude-vs-gemini
cd compare-gpt-vs-claude-vs-gemini
Set your API keys:
export OPENAI_API_KEY=your-openai-key
export ANTHROPIC_API_KEY=your-anthropic-key
export GOOGLE_API_KEY=your-google-key
Run the evaluation:
npx promptfoo@latest eval
View the results:
npx promptfoo@latest view
Source README
compare-gpt-vs-claude-vs-gemini (GPT vs Claude vs Gemini Comparison)
This example compares OpenAI's GPT-5.4, Anthropic's Claude Sonnet 4.6, and Google's Gemini 3.1 Pro Preview on riddle-solving tasks with cost, latency, and quality assertions.
You can run this example with:
npx promptfoo@latest init --example compare-gpt-vs-claude-vs-gemini
cd compare-gpt-vs-claude-vs-gemini
See the guide for more details.
Setup
Set the required environment variables:
export OPENAI_API_KEY=your-openai-key
export ANTHROPIC_API_KEY=your-anthropic-key
export GOOGLE_API_KEY=your-google-key
Run
npx promptfoo@latest eval
View
npx promptfoo@latest view
FAQ
Common questions
Discussion
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