What is G-Eval and when should I use it?

G-Eval is an LLM-graded evaluation method (based on arxiv 2303.16634) for scoring model output quality. Use it when you need LLM-based grading; if a simpler deterministic assertion like string matching or regex already captures what you need to check, G-Eval is not necessary.

How do I set up and run this G-Eval example?

Run `npx promptfoo@latest init --example eval-g-eval`, then navigate to the `eval-g-eval` directory and execute `promptfoo eval` to run the evaluation.

What configuration file does G-Eval use?

G-Eval is configured in `promptfooconfig.yaml` as an LLM-graded assertion that relies on a grading LLM provider to score outputs.

Who is this prompt chain intended for?

This is designed for promptfoo users who want to apply the G-Eval LLM-based grading method to evaluate and score output quality.

Prompt Chain

Evaluate and Refine AI Model Outputs

Name: Eval G Eval
Availability: OnlineOnly
Author: Promptfoo

A promptfoo workflow example that demonstrates how to use G-Eval, referencing the framework from the 2303.16634 paper.

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Updated 10 days ago

Source checked Sep 10, 2026

Version 0.123.0

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Why it matters

Automate the evaluation of AI model outputs against a set of criteria, providing structured feedback for iterative improvement.

Outcomes

What it gets done

Define evaluation metrics and criteria.

Run AI model outputs through evaluation prompts.

Analyze and summarize evaluation results.

Generate refined outputs or code based on feedback.

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-eval-g-eval | 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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Overview

Eval G Eval

This workflow demonstrates how to use G-Eval with promptfoo. G-Eval references the research paper arxiv.org/abs/2303.16634. The example runs through promptfoo's standard eval command with configuration in YAML. Use this when you want to explore G-Eval within promptfoo's evaluation framework. The example provides a starting configuration for running G-Eval evaluations.

What it does

This prompt chain demonstrates how to use G-Eval with promptfoo. G-Eval references the academic paper arxiv.org/abs/2303.16634. The example provides a starting configuration that you can run through promptfoo's evaluation command.

When to use - and when NOT to

Use this workflow when you want to explore G-Eval within the promptfoo testing framework. It provides a working example configuration to get started.

Do not use this if you need a different evaluation approach or if you're looking for evaluation methods other than G-Eval.

Inputs and outputs

You provide a promptfooconfig.yaml configuration file. The workflow runs evaluations using the promptfoo eval command.

How to use

Initialize the example workflow:

npx promptfoo@latest init --example eval-g-eval
cd eval-g-eval

Then run the evaluation:

promptfoo eval

The configuration lives in promptfooconfig.yaml where you define your evaluation parameters and test scenarios.

Integrations

This workflow uses promptfoo and demonstrates G-Eval integration.

Who it's for

This is built for users who want to explore G-Eval within promptfoo's evaluation framework.

Source README

eval-g-eval (G Eval)

You can run this example with:

npx promptfoo@latest init --example eval-g-eval
cd eval-g-eval

Usage

This example shows how you can use G-Eval with promptfoo

Configure in promptfooconfig.yaml. Run with:

promptfoo eval

FAQ

Common questions

Discussion