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LCM Dreamshaper v7

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LCM Dreamshaper v7 is an open-weights image model from SimianLuo (LCM authors), released October 2023. Its published size is 0.86B parameters. Licence: mit.

Catalogue identity notes

Latent consistency model distilled from Dreamshaper v7 (an SD 1.5 fine-tune); identity taken from the arena's own model registry. Memory estimated from the SD 1.x 860M UNet in fp32 (the card's default precision).

Model information sources

· Parameter count ↗

UNet only: HF Hub safetensors total for the official repo (pinned revision), 859,602,884 = unet/diffusion_pytorch_model.safetensors (SD v1 UNet plus LCM guidance-scale embedding). Text encoder and VAE not included. Observed 2026-10-07.

23.1±3.5#142 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 LCM Dreamshaper v7, out of 197 with a score.

#modelscorewhereRAMreleased
191Stable Diffusion v1.5 Stability AI26±2local~2.1GB2022-10
192OneCAT-3B Meituan (OneCAT team)24±5local~25GB2025-09
193LCM Dreamshaper v7 SimianLuo (LCM authors)23±4local~1.7GB2023-10
194InstructPix2Pix UC Berkeley (Brooks, Holynski, Efros)19±3local~2.6GB2023-01
195X-LXMERT UNC Chapel Hill17±4comparison only2020-09

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

$ what it's good at

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

Trails CogView2 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
GenAI-Arena text-to-image (Elo, 4 Jun 2024)817.0 ✎▃▃··▃·▃·█·▃▃ beats 0/8avg 1237▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%sharp

$ where to run it

Other ways to run it

version

  1. Run it as published · needs ~4.6 GB, NVIDIA only · from huggingface.co/SimianLuo (official)
    uv run --with diffusers --with transformers --with accelerate --with torch python -c "import torch; from diffusers import DiffusionPipeline; p=DiffusionPipeline.from_pretrained('SimianLuo/LCM_Dreamshaper_v7').to('cuda'); p(prompt='a cat holding a sign', num_inference_steps=4, guidance_scale=8.0).images[0].save('out.png')"

Official weights and documentation: huggingface.co/SimianLuo ↗

$ 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= 23.1

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data updated · sources and licences · json