ERNIE Image Models
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.
Explorar Modelos Líderes
Atlas Cloud le proporciona los últimos modelos creativos líderes en la industria.
Velocidad pico
Costo más bajo
| Modalidad | Descripción |
|---|---|
| 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. |
Nuevas funciones de ERNIE Image Models + Showcase
La combinación de modelos avanzados con la plataforma acelerada por GPU de Atlas Cloud ofrece velocidad, escalabilidad y control creativo inigualables para la generación de imágenes y videos.
Text-Heavy Visual Content with ERNIE-Image API
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.
Structured Layout Generation with ERNIE-Image API
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.
Bilingual Creative Expression with ERNIE-Image API
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.
Commercial Poster and Marketing Asset Creation with ERNIE-Image API
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.
What You Can Do with ERNIE-Image
Descubra casos de uso prácticos y flujos de trabajo que puede crear con esta familia de modelos — desde creación de contenido y automatización hasta aplicaciones de nivel producción.
Marketing and Advertising Production
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).
Publishing and Editorial Content
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.
Comic and Manga Creation
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.
UI/UX and Product Mockups
Generate realistic application screenshots, website mockups, and interface designs with readable text elements and coherent layout structures for presentation and prototyping.
Educational and Infographic Content
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.
Game Development and Concept Art
Develop character designs, environment concepts, and promotional artwork with cinematic quality and consistent style — supporting both indie and professional production pipelines.
Comparación de Modelos
Vea cómo se comparan los modelos de diferentes proveedores — compare rendimiento, precios y fortalezas únicas para tomar una decisión informada.
| 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 |
How to Use ERNIE Image Models on Atlas Cloud
Get started in minutes — follow these simple steps to integrate and deploy models through Atlas Cloud’s platform.
Create an Atlas Cloud Account
Sign up at atlascloud.ai and complete verification. New users receive free credits to explore the platform and test models.
Por Qué Usar ERNIE Image Models en Atlas Cloud
Combina modelos avanzados de ERNIE Image Models con la plataforma acelerada por GPU de Atlas Cloud, proporcionando rendimiento, escalabilidad y experiencia de desarrollo incomparables.
Rendimiento y Flexibilidad
Baja Latencia:
Inferencia optimizada por GPU para respuestas en tiempo real.
API Unificada:
Una sola integración para acceder a ERNIE Image Models, GPT, Gemini y DeepSeek.
Precios Transparentes:
Facturación por Token, soporta modo Serverless.
Empresa y Escala
Experiencia del Desarrollador:
SDK, análisis de datos, herramientas de ajuste fino y plantillas todo en uno.
Confiabilidad:
99.99% de disponibilidad, control de permisos RBAC, registros de cumplimiento.
Seguridad y Cumplimiento:
Certificación SOC 2 Type II, cumplimiento HIPAA, soberanía de datos en EE.UU.
FAQ
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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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.
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