Model overview
This is a GGUF quantized version of ERNIE-Image-Turbo. unsloth/ERNIE-Image-Turbo-GGUF uses Unsloth Dynamic 2.0 methodology for SOTA performance. - Important layers are upcasted to higher precision. - Uses tooling from ComfyUI-GGUF by city96. ERNIE-Image-Turbo is an open text-to-image generation model developed by the ERNIE-Image team at Baidu. It is the distilled release of ERNIE-Image, built on the same single-stream Diffusion Transformer (DiT) family and designed for fast generation with strong fidelity in only 8 inference steps. The model retains strong controllability in practical generation scenarios where accurate content realization matters as much as aesthetics. In particular, ERNIE-Image-Turbo remains strong on complex instruction following, text rendering, and structured image generation, making it well suited for posters, comics, multi-panel layouts, and other content creation tasks that require both visual quality and efficiency. It also supports a broad range of visual styles, including realistic photography, design-oriented imagery, and stylized aesthetic outputs. **Highlights:** - **Fast and efficient**: As the distilled checkpoint of ERNIE-Image, ERNIE-Image-Turbo delivers strong generation quality with only 8 inference steps, making it suitable for latency-sensitive applications. - **Text rendering**: ERNIE-Image-Turbo performs well on dense, long-form, and layout-sensitive text, making it a strong choice for posters, infographics, UI-like images, and other text-heavy visual content. - **Instruction following**: The model is able to follow complex prompts involving multiple objects, detailed relationships, and knowledge-intensive descriptions with strong reliability. - **Structured generation**: ERNIE-Image-Turbo is effective for structured visual tasks such as posters, comics, storyboards, and multi-panel compositions, where layout and organization are critical. - **Style coverage**: In addition to clean and readable design-oriented outputs, the model also supports realistic photography and distinctive stylized aesthetics, including softer and more cinematic visual tones. - **Practical deployment**: Thanks to its compact size, ERNIE-Image-Turbo
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。