ideogram-v3/remix
Remix an image with a prompt while keeping the original style in Ideogram 3.
Z Image Turbo Free: Ultra Fast Text-to-Image Generation & Design Output
tongyi-mai/z-image/turbo/text-to-image
Generate high-quality, photorealistic images from text instantly with Z Image Turbo's 6B-parameter engine, offering ultra-fast speed, precise text rendering, and versatile format output for creative professionals.
Idle
The rate is $0.005 per image.
Introduction to Z Image Turbo
Alibaba Tongyi MAI's Z Image Turbo generates photorealistic images from text at $0.005 per image, using 8-step, sub-second inference to deliver sharp 1024px results with reliable English and Chinese text rendering. Trading manual compositing and complex masking for a single-stream, few-step diffusion pipeline that preserves layout, subject consistency, and bilingual typography, Z Image Turbo streamlines iteration and reduces art-direction cycles, built for e-commerce teams, designers, and marketing workflows. For developers, Z Image Turbo on RunComfy can be used both in the browser and via an HTTP API, so you don’t need to host or scale the model yourself.
Ideal for: Brand-Consistent Ad Creatives | Multilingual Poster Design | Product Mockups at Scale
Creative Examples Made with Z Image Turbo
Reviews about Z Image Turbo on X
Model Overview
- Provider: Tongyi-MAI (Alibaba Tongyi Lab)
- Task: text-to-image
- Max Resolution/Duration: Up to ~3K px (typical 2K; 1024×1024 recommended on 16 GB VRAM)
- Summary: Z Image Turbo is an open, production-ready text-to-image model optimized for speed, low VRAM usage, and prompt fidelity. It generates photorealistic images with strong bilingual text rendering and follows layout/style instructions with only 8 inference steps, making it ideal for rapid iteration and cost-efficient pipelines.
Key Capabilities
Turbo-speed generation on commodity GPUs
- Requires only 8 inference steps (NFE) and reaches sub-second latency on enterprise GPUs while fitting within 16 GB VRAM.
- Delivers high throughput for prototyping, A/B testing, and batch creative runs without sacrificing stability.
Bilingual, scene-accurate text rendering
- Produces readable English and Chinese text within scenes (e.g., signage, posters, packaging) with strong typography.
- Reduces post-editing by accurately placing and shaping text in complex compositions.
High prompt and layout fidelity
- Adheres closely to object, style, lighting, and layout instructions.
- Improves creative control for storyboards, product shots, and branded visuals where spatial relationships matter.
Input Parameters
Core Prompt
| Parameter | Type | Default/Range | Description |
|---|---|---|---|
| prompt | string | default: "" | Natural-language description of the image to generate. Provide subjects, scene, lighting, style, and any exact text to render. |
Dimensions & Sampling
| Parameter | Type | Default/Range | Description |
|---|---|---|---|
| image_size | string (choice/custom) | default: landscape_4_3; choices: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9, Custom | Select a preset aspect ratio or choose Custom to specify width/height. Use 1024×1024 on ≥16 GB VRAM; reduce if memory-constrained. |
| num_inference_steps | integer | default: 8 | Number of denoising steps. Z Image Turbo is optimized for 8 steps for speed and stability. |
| seed | integer | default: 0 | Random seed for reproducibility. Use a fixed seed to replicate results; 0 or unset for random. |
| num_images | integer | default: 1 | Number of images to generate per request. Increases compute proportionally. |
How Z Image Turbo compares to other models
- Vs Seedream 4.5: Compared to Seedream 4.5, Z Image Turbo delivers faster cold-start and lower VRAM usage with 8-step inference. Seedream 4.5 provides a higher ceiling for complex typography/layout and native 4K pipelines. Ideal Use Case: pick Z Image Turbo for rapid prototyping, cost-sensitive deployments, and bilingual signage where speed matters.
- Vs FLUX.2 Pro: Compared to FLUX.2 Pro, Z Image Turbo delivers sub-second generation on 16 GB GPUs and simpler scaling for batch throughput. FLUX.2 Pro generally offers richer photorealistic polish and cinematic aesthetics. Ideal Use Case: choose Z Image Turbo when you need fast, controllable outputs with efficient infrastructure.
- Vs Nano Banana Pro: Compared to Nano Banana Pro, Z Image Turbo balances good text clarity with high throughput and low latency. Nano Banana Pro often leads in ultra-precise small-font typography and realism. Ideal Use Case: adopt Z Image Turbo when speed and resource efficiency outweigh maximum typographic perfection.
- Key Improvements (Turbo): 8-step fast sampling, sub-second latency on enterprise GPUs, robust bilingual text rendering, strong prompt adherence, and permissive Apache-2.0 licensing for commercial use.
API Integration
Developers can seamlessly integrate Z Image Turbo using the RunComfy API with standard HTTP requests. The request/response format is consistent across RunComfy models, enabling quick drop-in adoption, easy parameter tuning, and reproducible seeds for deterministic workflows.
Note: API Endpoint for Z Image Turbo
Official resources and licensing
- Official Website: https://huggingface.co/Tongyi-MAI/Z-Image-Turbo
- Documentation: https://zimage.net/docs
- Paper: https://arxiv.org/abs/2511.22699
- License: Apache-2.0. Commercial use is permitted under the license; verify any additional enterprise terms with the provider if required.
Note: You can try the Image to Image version or use customized LoRA models on Z Image Turbo Loras: https://www.runcomfy.com/models/tongyi-mai/z-image/turbo/image-to-image/lora, https://www.runcomfy.com/models/tongyi-mai/z-image/turbo/controlnet/lora
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Frequently Asked Questions
What is Z Image Turbo and what makes its text-to-image engine special?
Z Image Turbo is a high-speed text-to-image generation model created by Tongyi-MAI under Alibaba’s AI research division. Its turbo architecture enables near real-time image creation with strong fidelity to prompts, supporting both English and Chinese text rendering.
Who are the ideal users for Z Image Turbo’s text-to-image capabilities?
Z Image Turbo’s text-to-image engine is ideal for designers, developers, artists, and marketing professionals who need fast, high-quality visuals. It suits creative agencies, game studios, and app developers embedding image generation into workflows or interactive platforms.
How much does it cost to use Z Image Turbo for text-to-image generation?
Access to Z Image Turbo’s text-to-image service is available via Runcomfy’s AI Playground, where users spend credits to generate images. New users typically receive free trial credits, and ongoing credit usage is governed by the ‘Generation’ section on the platform’s pricing page.
How does Z Image Turbo differ from earlier text-to-image models?
Unlike earlier text-to-image models with larger parameter counts, Z Image Turbo uses about 6 billion parameters and advanced distillation methods to maintain image quality while delivering much faster performance on modest hardware.
What image formats and outputs does Z Image Turbo’s text-to-image generator support?
Z Image Turbo supports output in multiple formats, including PNG, JPEG, and WEBP, through its text-to-image pipeline. Users can also adjust image size, aspect ratio, and seed configuration to match specific creative needs.
Is Z Image Turbo open source and can it be used commercially for text-to-image content?
Yes, Z Image Turbo’s text-to-image framework is released under the permissive Apache 2.0 license, allowing commercial use. This makes it appealing to businesses that require flexible, legally compliant AI-based content generation.
What platforms or environments support Z Image Turbo’s text-to-image model?
Z Image Turbo can be accessed online through platforms like fal.ai and Runcomfy, both of which support browsers on desktop and mobile. It can also integrate with APIs and SDKs for developers who want to embed its text-to-image generation into applications.
What are the main benefits of using Z Image Turbo compared to other text-to-image models?
Z Image Turbo offers a rare mix of speed, clarity, and instruction fidelity in its text-to-image generation. It’s optimized for lower VRAM usage, enabling near-instant results without compromising quality, even on mid-range GPUs.
Does Z Image Turbo’s text-to-image feature have any limitations?
While Z Image Turbo’s text-to-image generation is exceptionally fast, the results depend on hardware performance and input complexity. Users seeking ultra-detailed or artistic styles may occasionally require post-processing or additional prompt refinement.
How can users give feedback about Z Image Turbo’s text-to-image performance?
Users can share feedback or improvement ideas about Z Image Turbo’s text-to-image performance by emailing hi@runcomfy.com. The developers welcome insights to refine model tuning and user experience.
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