

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 為您提供最新的行業領先創意模型。
最低成本
| 模態 | 描述 |
|---|---|
| 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. |
將先進模型與 Atlas Cloud 的 GPU 加速平台相結合,為圖像和視頻生成提供無與倫比的速度、可擴展性和創意控制。

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.
探索使用該模型家族可以構建的實際應用場景和工作流 — 從內容創作、自動化到生產級應用。
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.
查看不同廠商的模型表現 — 對比效能、價格和獨特優勢,做出明智決策。
| 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 |
幾分鐘即可上手 — 按照以下簡單步驟,透過 Atlas Cloud 平台整合和部署模型。
在 atlascloud.ai 註冊並完成驗證。新用戶可獲得免費額度,用於探索平台和測試模型。
將先進的 ERNIE Image Models 模型與 Atlas Cloud 的 GPU 加速平台相結合,提供無與倫比的效能、可擴展性和開發體驗。
低延遲:
GPU 最佳化推理,實現即時回應。
統一 API:
一次整合,暢用 ERNIE Image Models、GPT、Gemini 和 DeepSeek。
透明定價:
按 Token 計費,支援 Serverless 模式。
開發者體驗:
SDK、資料分析、微調工具和模板一應俱全。
可靠性:
99.99% 可用性、RBAC 權限控制、合規日誌。
安全與合規:
SOC 2 Type II 認證、HIPAA 合規、美國資料主權。
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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