<a target="_blank" rel="ugc" href="https://huggingface.co/baidu/ERNIE-Image">HF</a> | <a target="_blank" rel="ugc" href="https://civarchive.com/api/download/models/2439129?type=Model&amp;format=SafeTensor&amp;size=pruned&amp;fp=fp8">VAE</a> |<a target="_blank" rel="ugc" href="https://civarchive.com/api/download/models/2857928?type=Training%20Data">Basic workflow</a> in the zip file. Turbo CFG: 1 Steps: 8ERNIE-Image is an 8B parameter text-to-image model from Baidu.It excels at complex prompt understanding, clear text rendering inside images, and structured layouts like posters, comics, and multi-panel designs.Includes a built-in Prompt Enhancer that turns short inputs into detailed descriptions. Works great in English and Chinese.Apache 2.0 licenseThe model is mirrored here for convenience.

Ernie-Image

ernieImage_turbo.safetensors

ernieImage_turbo_trainingData.zip

Turbo

txt_enc Mistral-3-3b

BF16

Originally Posted: <a target="_blank" rel="ugc" href="https://ernie.baidu.com/blog/posts/ernie-image/">https://ernie.baidu.com/blog/posts/ernie-image</a>ERNIE-Image is an open text-to-image model from the ERNIE-Image team at Baidu. Built on a single-stream Diffusion Transformer (DiT) with 8B parameters in a latent diffusion (LDM) framework, it ships with a lightweight Prompt Enhancer that expands brief inputs into richer, more structured prompts to better unlock the model's capabilities. With only 8B DiT parameters, ERNIE-Image achieves state-of-the-art performance among open weights text-to-image models — and it is built not just for visual appeal, but for controllability: accurate content depiction matters as much as aesthetics. In practice, it excels at complex instruction following, precise text rendering, and structured image generation — areas where many existing open weights models still fall short.<h3 id="key-features">Key Features</h3><ul><li>•Competitive performance at compact scale: With only 8B DiT parameters, ERNIE-Image remains competitive with substantially larger models and achieves leading performance among open weights models on several challenging benchmarks.</li><li>•Precise text rendering: ERNIE-Image handles dense, long-form, and layout-sensitive text especially well, producing readable and faithful results in Chinese, English, and other languages.</li><li>•Robust instruction following: The model reliably handles complex prompts, multi-object relations, and knowledge-intensive descriptions, making it well suited for tasks that demand fine-grained control.</li><li>•Structured visual generation: ERNIE-Image is especially effective on images with clear layout or narrative structure — posters, manga/anime storyboards, multi-panel compositions, and cohesive multi-element visuals.</li><li>•Broad stylistic range: Beyond clean graphic design and illustration-style outputs, the model supports realistic photography and distinctive stylized aesthetics, including softer, more cinematic and film-like tones.</li><li>•Easy to deploy and adapt: Thanks to its compact size, ERNIE-Image runs on consumer-grade hardware (24G VRAM), bringing high-quality image generation within reach for research and production use. The moderate parameter count also makes fine-tuning and adaptation straightforward for researchers and developers.</li></ul>

ERNIE‑Image

ernieImage_imageTurbo.safetensors

Image Turbo

Image

ERNIE-Image

ernie-image-turbo.safetensors

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```
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```
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tradada/ERNIE-Image-Turbo

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