This is not my model. Don't ask me questions. I don't know the answers.

Go to the official LongCat-Image repo for answers.

Edit Turbo model repo:

• Steps: 8 (it's a lie! Use at least 20! But it's fast)

• CFG: 1

• Text Encoder: qwen_2.5_vl_7b_fp8_scaled.safetensors

• VAE: flux_ae.safetensors

Base model repo:

• Steps: 50

• CFG: 4

• Text Encoder: qwen_2.5_vl_7b_fp8_scaled.safetensors

• VAE: flux_ae.safetensors

I've only uploaded the model here as a way to tag the images I generate with it. It will most likely be taken down once the official owners upload their own version, so be warned.

The following is the original README as of time of publishing.

We introduce LongCat-Image, a pioneering open-source and bilingual (Chinese-English) foundation model for image generation, designed to address core challenges in multilingual text rendering, photorealism, deployment efficiency, and developer accessibility prevalent in current leading models.

Key Features

• 🌟 Exceptional Efficiency and Performance: With only 6B parameters, LongCat-Image surpasses numerous open-source models that are several times larger across multiple benchmarks, demonstrating the immense potential of efficient model design.

• 🌟 Powerful Chinese Text Rendering: LongCat-Image demonstrates superior accuracy and stability in rendering common Chinese characters compared to existing SOTA open-source models and achieves industry-leading coverage of the Chinese dictionary.

• 🌟 Remarkable Photorealism: Through an innovative data strategy and training framework, LongCat-Image achieves remarkable photorealism in generated images.

🎨 Showcase