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Playground v2 (1024px aesthetic)

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Playground v2 (1024px aesthetic) is an open-weights image model from Playground, released December 2023. Its published size is 2.57B parameters. Licence: playground-v2-community.

Catalogue identity notes

playgroundai/playground-v2-1024px-aesthetic. No parameter count on the card; memory estimated as for SDXL 1.0 (same SDXL-architecture UNet).

Model information sources

· Parameter count ↗

UNet only: HF Hub safetensors total for the official repo (pinned revision), 2,567,463,684 = unet/diffusion_pytorch_model.safetensors (SDXL-architecture UNet). The two CLIP text encoders and the VAE are not included. Observed 2026-10-07.

41.2±3.5#104 of 144 image modelsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

Score within the LMArena text-to-image comparison set only.

$ how it compares

The image models ranked either side of Playground v2 (1024px aesthetic), out of 197 with a score.

#modelscorewhereRAMreleased
137Stable Diffusion 3.5 Large Stability AI42±1api $0.065/image +local~5.4GB2024-10
138Show-o2 7B Show Lab, NUS42±3local~23GB2025-06
139Playground v2 (1024px aesthetic) Playground41±4local~4.9GB2023-12
140Playground v2.5 Playground41±2local~8.8GB2024-02
141Stable Diffusion 3.5 Medium Stability AI41±3api $0.035/image +local~20GB2024-10

see all image models · find the ones that fit your machine

$ what it's good at

text to image▂▅▅▃▄▄█▃▁▂▁▁ #81 of 126 * · 95% of its score · 1 test

Beats Latent Diffusion text2img-large (LDM-KL-8-G, LAION-400M), VQ-Diffusion (ITHQ), FLUX.1 Kontext [dev] here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
GenAI-Arena text-to-image (Elo, 4 Jun 2024)1101.0 ✎▃▃··▃·▃·█·▃▃ beats 7/8avg 1237▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%sharp

$ where to run it

Other ways to run it

version

  1. Run it as published · needs ~8.9 GB, NVIDIA only · from huggingface.co/playgroundai (official)
    uv run --with diffusers --with transformers --with accelerate --with torch python -c "import torch; from diffusers import DiffusionPipeline; p=DiffusionPipeline.from_pretrained('playgroundai/playground-v2-1024px-aesthetic', torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False, variant='fp16').to('cuda'); p(prompt='a cat holding a sign', guidance_scale=3.0).images[0].save('out.png')"

Official weights and documentation: huggingface.co/playgroundai ↗

$ how the score was worked out · GenAI Arena: An Open Evaluati… 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
GenAI Arena: An Open Evaluation Platform for Generative Models (arXiv v3)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%CC-BY-4.0
prior · pull toward the middle▇▇ 5%
weighted average= 41.2

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json