Longcat Image is an AI image generation and editing platform built on the Meituan LongCat-Image 6B model. It renders Chinese and English text inside images with unusual sharpness, produces photorealistic results, and includes a full editing toolkit for creators and marketers.
Text to image generation. Image editing with natural language prompts. Sharp Chinese and English text rendering inside images. Photorealistic output quality. Full set of editing tools.
E-commerce product images. Social media creatives and ad banners. Posters with embedded text. Marketing visuals for campaigns.

Really like that this is built on Meituan's open-sourced LongCat-Image 6B model instead of a closed one — 6B is a pretty small footprint compared to most competing image models, and the Chinese text rendering samples on the page look noticeably cleaner than what I've seen from bigger closed models. Question on the multi-round editing: how does it preserve facial identity/subject consistency across rounds — is that built into the base model's training, or is there a separate identity-locking step? A before/after strip of the same subject through 3-4 edit rounds on the landing page would make that claim much easier to trust at a glance.
Going with Meituan's open 6B model instead of a bigger proprietary one is an interesting bet, especially given the note that it renders Chinese text more cleanly than some larger competitors text rendering is usually where image models fall apart. Is the compactness mainly a cost/speed tradeoff for you, or did you find the smaller model was actually competitive on quality too?
Great combination of high-quality image generation and precise text rendering. The natural-language editing makes creating polished marketing and e-commerce visuals much faster. 🔗 https://pixprep.online/


Really like that this is built on Meituan's open-sourced LongCat-Image 6B model instead of a closed one — 6B is a pretty small footprint compared to most competing image models, and the Chinese text rendering samples on the page look noticeably cleaner than what I've seen from bigger closed models. Question on the multi-round editing: how does it preserve facial identity/subject consistency across rounds — is that built into the base model's training, or is there a separate identity-locking step? A before/after strip of the same subject through 3-4 edit rounds on the landing page would make that claim much easier to trust at a glance.
Going with Meituan's open 6B model instead of a bigger proprietary one is an interesting bet, especially given the note that it renders Chinese text more cleanly than some larger competitors text rendering is usually where image models fall apart. Is the compactness mainly a cost/speed tradeoff for you, or did you find the smaller model was actually competitive on quality too?
Great combination of high-quality image generation and precise text rendering. The natural-language editing makes creating polished marketing and e-commerce visuals much faster. 🔗 https://pixprep.online/

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