VybBench Is Now on GitHub

Coco Labs, the makers of Vyb, released VybBench 1.0 on GitHub, a design-fidelity benchmark built from 145 fonts, 100 colors and 200 edits, with each model performing each task three times and every generation scored individually. The benchmark compares ChatGPT Image (gpt-image-2.5-sunburst), Meta Muse and Recraft v4.1 alongside Coco Labs' own Vyb 1.0, with prompts and run results published in a HuggingFace dataset and scoring code installable via pip. Coco Labs disclosed it built the benchmark, and developers can add a model by implementing generate and edit methods and running the run, judge and score commands.

Almost isn't good enough. VybBench measures how well models maintain design fidelity by comparing how effectively they generate specific fonts and colors, and perform non-destructive edits. Our dataset consists of 145 fonts, 100 colors, and 200 edits. We have each model perform each task three times and score each generation individually. We compare top image generation models: ChatGPT Image gpt-image-2.5-sunburst , Meta Muse, and Recraft v4.1. We also report the results for Vyb 1.0 https://cocolabs.ai/vyb . Full Disclosure: VybBench was built by Coco Labs, the makers of Vyb. The full methodology and rationale are in the launch post https://cocolabs.ai/blog/introducing-vybbench . This repo contains the code for scoring any model. The prompts and the results from our runs are available in the HuggingFace Dataset: https://huggingface.co/datasets/cocolabs/vybbench https://huggingface.co/datasets/cocolabs/vybbench . They are downloaded automatically. pip install -e . vybbench score We have made it easy for you to test any model simply by doing the following: python from vybbench.model import Model, Start class MyModel Model : name = "mymodel" def generate self, prompt: str, width: int, height: int - bytes: ... def edit self, instruction: str, start: Start - bytes: ... vybbench run --model mypkg.mymodel:MyModel vybbench judge vybbench score Our judging and scoring is based on the returned PNGs. Starts contain both the starting png and the starting svg. Use whichever is better for your model. We are happy to include your model. Please create an issue with the model code. @misc{vybbench2026, title = {VybBench 1.0: A Design Fidelity Benchmark}, author = {{Coco Labs}}, year = {2026}, url = {https://huggingface.co/datasets/cocolabs/vybbench} }