---
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: image1
    dtype: image
  - name: image2
    dtype: image
  - name: model1
    dtype: string
  - name: model2
    dtype: string
  - name: weighted_results_image1_preference
    dtype: float32
  - name: weighted_results_image2_preference
    dtype: float32
  - name: detailed_results_preference
    dtype: string
  - name: weighted_results_image1_coherence
    dtype: float32
  - name: weighted_results_image2_coherence
    dtype: float32
  - name: detailed_results_coherence
    dtype: string
  - name: weighted_results_image1_alignment
    dtype: float32
  - name: weighted_results_image2_alignment
    dtype: float32
  - name: detailed_results_alignment
    dtype: string
  splits:
  - name: train
    num_bytes: 32462670063.0
    num_examples: 13000
  download_size: 6565441182
  dataset_size: 32462670063.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cdla-permissive-2.0
task_categories:
- text-to-image
- image-to-text
- image-classification
- reinforcement-learning
language:
- en
tags:
- Human
- Preference
- Coherence
- Alignment
- country
- language
- flux
- midjourney
- dalle3
- stabeldiffusion
- alignment
- flux1.1
- flux1
- imagen3
- aurora
- lumina
- recraft
- recraft v2
- ideogram
- frames
- reve ai
- halfmoon
- hidream
- Imagen4
- imagen-4.0-ultra-generate-exp-05-20
size_categories:
- 100K<n<1M
pretty_name: Hidream-I1-full vs. Halfmoon / OpenAI 4o / Ideogram V2 / Recraft V2 / Lumina-15-2-25 /
  Frames-23-1-25 / Aurora / imagen-3 / Flux-1.1-pro / Flux-1-pro / Dalle-3 / Midjourney-5.2
  / Stabel-Diffusion-3 - Human Preference Dataset
---

<style>

.vertical-container {
    display: flex;  
    flex-direction: column;
    gap: 60px;  
}

.image-container img {
  max-height: 250px; /* Set the desired height */
  margin:0;
  object-fit: contain; /* Ensures the aspect ratio is maintained */
  width: auto; /* Adjust width automatically based on height */
  box-sizing: content-box;
}

.image-container {
  display: flex; /* Aligns images side by side */
  justify-content: space-around; /* Space them evenly */
  align-items: center; /* Align them vertically */
  gap: .5rem
}

  .container {
    width: 90%;
    margin: 0 auto;
  }

  .text-center {
    text-align: center;
  }

  .score-amount {
margin: 0;
margin-top: 10px;
  }

  .score-percentage {Score: 
    font-size: 12px;
    font-weight: semi-bold;
  }
  
</style>

# Rapidata Imagen 4 Preference

<a href="https://www.rapidata.ai">
<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/jfxR79bOztqaC6_yNNnGU.jpeg" width="400" alt="Dataset visualization">
</a>

This T2I dataset contains over 195k human responses from over 70k individual annotators, collected in just ~1 Day using the [Rapidata Python API](https://docs.rapidata.ai), accessible to anyone and ideal for large scale evaluation.
Evaluating Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) across three categories: preference, coherence, and alignment.

Explore our latest model rankings on our [website](https://www.rapidata.ai/benchmark).

If you get value from this dataset and would like to see more in the future, please consider liking it ❤️

## Overview

This T2I dataset contains over 195k human responses from over 70k individual annotators, collected in just ~1 Day.
Evaluating Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) across three categories: preference, coherence, and alignment.

The evaluation consists of 1v1 comparisons between Imagen 4 (imagen-4.0-ultra-generate-exp-05-20) and 15 other models: Hidream I1 full, Halfmoon-4-4-2025, OpenAI 4o-26-3-25, Ideogram V2, Recraft V2, Lumina-15-2-25, Frames-23-1-25, Imagen-3, Flux-1.1-pro, Flux-1-pro, DALL-E 3, Midjourney-5.2, Stable Diffusion 3, Aurora and Janus-7b.
> **Note:** The number following the model name (e.g., Halfmoon-4-4-2025) represents the date (April 4, 2025) on which the images were generated to give an understanding of what model version was used.
## Alignment

The alignment score quantifies how well an video matches its prompt. Users were asked: "Which image matches the description better?".

<div class="vertical-container">
  <div class="container">
   <div class="text-center">
      <q>A blue cup and a green cell phone.</q>
    </div>
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4 </h3>
        <div class="score-percentage">Score: 100%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/8JcDYOeviHCwVQo0vLMB-.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Frames-23-1-25 </h3>
        <div class="score-percentage">Score: 0%</div>
        <img src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/WmHuNZY4M_NWUMSTSofNL.jpeg" width=500>
      </div>
    </div>
  </div>

  <div class="container">
   <div class="text-center">
      <q>A person is walking with a guidebook and taking a tour of a historic site.</q>
    </div>
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4</h3>
        <div class="score-percentage">Score: 0%</div>
        <img  src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/RiyfAra-C5QcCT9lDiohg.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Aurora</h3>
        <div class="score-percentage">Score: 100%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/SPbiu_SE8S4vRv6p0OZHo.jpeg" width=500>
      </div>
    </div>
  </div>
</div>

## Coherence

The coherence score measures whether the generated video is logically consistent and free from artifacts or visual glitches. Without seeing the original prompt, users were asked: "Which image has **more** glitches and is **more** likely to be AI generated?"

<div class="vertical-container">
  <div class="container">
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4 </h3>
        <div class="score-percentage">Glitch Rating: 0%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/X2jimr0Icoqb4RlX6jG1j.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Stable Diffusion 3 </h3>
        <div class="score-percentage">Glitch Rating: 100%</div>
        <img src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/UUllaDc48oxLXxeXbF_CD.jpeg" width=500>
      </div>
    </div>
  </div>

   <div class="container">
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4 </h3>
        <div class="score-percentage">Glitch Rating: 100%</div>
        <img src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/1a5dQzX2XxTLIUcgimocy.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Ideogram</h3>
        <div class="score-percentage">Glitch Rating: 0%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/pI5B7RxysOcUhVEzdqHFq.jpeg" width=500>
      </div>
    </div>
  </div>   
</div>

## Preference

The preference score reflects how visually appealing participants found each image, independent of the prompt. Users were asked: "Which image do you prefer?"

<div class="vertical-container">
  <div class="container">
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4</h3>
        <div class="score-percentage">Score: 81.83%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/b3ny4C5fRdfnoIlK3ocFi.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Frames-23-1-25</h3>
        <div class="score-percentage">Score: 18.17%</div>
        <img src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/KDJSo6s6FMKpXiovP03cJ.jpeg" width=500>
      </div>
    </div>
  </div>

   <div class="container">
    <div class="image-container">
      <div>
        <h3 class="score-amount">Imagen 4 </h3>
        <div class="score-percentage">Score: 27.42%</div>
        <img  src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/-g7n1pP8QRU0Gcv-iKF4q.jpeg" width=500>
      </div>
      <div>
        <h3 class="score-amount">Frames-23-1-25 </h3>
        <div class="score-percentage">Score: 72.58%</div>
        <img style="border: 3px solid #18c54f;" src="https://cdn-uploads.huggingface.co/production/uploads/664dcc6296d813a7e15e170e/BMXzpF1loC3wVfWuyj5VX.jpeg" width=500>
      </div>
    </div>
  </div>
</div>

## About Rapidata

Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit [rapidata.ai](https://www.rapidata.ai/) to learn more about how we're revolutionizing human feedback collection for AI development.