

ERNIE-Image is an open-weight text-to-image model developed by the ERNIE-Image Team at Baidu, built on a single-stream Diffusion Transformer (DiT) with 8B parameters and paired with a lightweight Prompt Enhancer that rewrites short prompts into richer, more structured descriptions before passing them to the diffusion backbone. NYU Shanghai RITS Released on April 15, 2026 under the Apache 2.0 license, it transforms natural language descriptions into detailed imagery with particular strength in text rendering and structured layout generation. ERNIE-Image is designed not only for strong visual quality, but for controllability in practical generation scenarios where accurate content realization matters as much as aesthetics — making it well-suited for commercial posters, comics, multi-panel layouts, and other content creation tasks that require both visual quality and precise control.
Atlas Cloudは、業界をリードする最新のクリエイティブモデルを提供します。
最低コスト
| モダリティ | 説明 |
|---|---|
| ERNIE-Image API (Text To Image) | The flagship quality-focused model. The SFT variant runs at guidance scale 4.0 with 50 inference steps for maximum quality 24-7 Press Release — optimized for final production assets including posters, editorial graphics, and commercial layouts. |
| ERNIE-Image Turbo API (Text To Image) | The Turbo variant, optimized through DMD (Diffusion Model Distillation) and reinforcement learning, compresses inference steps from 50 to 8, achieving 6x+ speed improvement while maintaining high-quality output. Stable Learn Ideal for rapid iteration and high-volume workflows. |
先進的なモデルと Atlas Cloud の GPU アクセラレーションプラットフォームを組み合わせ、画像・動画生成において比類のない速度、拡張性、クリエイティブコントロールを実現します。

ERNIE-Image leads the open-source field with a LongTextBench score of 0.9733 — rendering accurate text inside images including comic speech bubbles, poster headlines, infographic labels, and UI mockup copy. If your use case requires legible, correctly-spelled text baked into the image, ERNIE-Image is the clear leader.

The codebase exposes generation, edit, composite, and upscale primitives so designers can centralize an asset pipeline. Let's Data Science By understanding spatial relationships and grid-based arrangements, it generates coherent multi-panel sequential artwork and formatted designs.

Both English and Chinese prompts are natively supported through the same encoder pipeline 24-7 Press Release, capturing cultural nuances and idiomatic expressions across languages for authentic visual storytelling.

ERNIE-Image generates print-ready marketing materials with embedded typography, product placements, and professional layouts. For creatives and product teams, ERNIE-Image lowers the barrier to production-grade poster, comic, storyboard, and UI asset generation without license friction.
このモデルファミリーで構築できる実用的なユースケースとワークフローを発見 — コンテンツ作成や自動化から本番グレードのアプリケーションまで。
Generate campaign-ready posters, banners, and promotional materials with embedded text, product visuals, and professional layouts at high throughput — suitable for both quick drafts (Turbo) and final assets (Standard).
Create book covers, magazine illustrations, and editorial graphics with precise typography and artistic consistency. The industry-leading text rendering makes it ideal for text-heavy publication designs.
ERNIE-Image lowers the barrier to production-grade comic, storyboard, and sequential art generation Let's Data Science with consistent character representation and integrated dialogue — streamlining production for independent creators and studios.
Generate realistic application screenshots, website mockups, and interface designs with readable text elements and coherent layout structures for presentation and prototyping.
ERNIE-Image performs strongly on complex instruction following and text rendering GitHub, making it well-suited for visually engaging educational materials, data visualizations, and explainer graphics combining imagery with clear, legible annotations.
Develop character designs, environment concepts, and promotional artwork with cinematic quality and consistent style — supporting both indie and professional production pipelines.
異なるプロバイダーのモデルを比較 — パフォーマンス、料金、独自の強みを確認して最適な選択を。
| Model | Reference Image Limit | Output Num | Resolution | Aspect Ratio |
|---|---|---|---|---|
| ERNIE-Image | 0 (T2I) | 1–8 | 1024×1024 | 1:1 |
| ERNIE-Image Turbo | 0 (T2I) | 1–8 | 1024×1024 | 1:1 |
| Qwen-Image | 3 | 1–6 | 512P~2K | Width[512, 2048]px; Height[512, 2048]px |
| Flux.1 | 1 | 1 | 256P~4K | Width[256, 4096]px; Height[256, 4096]px |
| Seedream 5.0 | 14 | 1~15 | 2K~4K+ | 1:1 3:2 2:3 3:4 4:3 4:5 5:4 9:16 16:9 21:9 |
数分で始められます — 以下の簡単なステップに従って、Atlas Cloud プラットフォームでモデルを統合・デプロイしましょう。
atlascloud.ai でサインアップし、認証を完了します。新規ユーザーには無料クレジットが付与され、プラットフォームの探索やモデルのテストに使用できます。
高度なERNIE Image ModelsモデルとAtlas CloudのGPU加速プラットフォームを組み合わせることで、比類のないパフォーマンス、スケーラビリティ、開発者エクスペリエンスを提供。
低レイテンシ:
リアルタイム推論のためのGPU最適化推論。
統合API:
1つの統合でERNIE Image Models、GPT、Gemini、DeepSeekを実行。
透明な料金:
サーバーレスオプション付きの予測可能なtoken単位の課金。
開発者エクスペリエンス:
SDK、分析、ファインチューニングツール、テンプレート。
信頼性:
99.99%の稼働率、RBAC、コンプライアンス対応ロギング。
セキュリティとコンプライアンス:
SOC 2 Type II、HIPAA準拠、米国内のデータ主権。
A: ERNIE-Image achieves top-tier image rendering on consumer-grade GPUs. It excels in following complex instructions and multi-language text rendering, with comprehensive capabilities comparable to top-tier closed-source models. CnTechPost Its particular strengths in text rendering (LongTextBench 0.9733) and structured layout generation for comics, posters, and infographics set it apart from general-purpose open models.
A: Both English and Chinese text rendering score above 0.96 on LongTextBench. FLUX.2 collapses in Chinese scenarios (scoring 0.2183), while ERNIE-Image remains stable Stable Learn — handling Simplified Chinese, Traditional Chinese, and mixed bilingual content with high accuracy.
Yes. ERNIE-Image is released under the Apache 2.0 license GitHub, which permits commercial use, modification, and distribution. Generated images can be used in advertising, merchandise, publications, and commercial applications.
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