Z-Image Turbo

AI Image Editing Model

$ · 0.5¢

Tongyi-MAI's 6-billion parameter distilled text-to-image model optimized for speed, achieving high-quality generation in 8 steps or fewer with support for bilingual text rendering

2048 x 2048
Max Resolution
Input / Output
Text Image Image
Active

Details

Model ID
z-image-turbo
Creator
Alibaba
Family
z-image
Tags
image-generation text-to-image fast open-weights
// Get Started

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Access z-image-turbo via our unified API.

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Providers & Pricing (4)

Z-Image Turbo is available from 4 providers, with per-image pricing starting at $0.005 through fal.ai.

fal.ai
fal/z-image-turbo-edit
Provider Model ID: fal-ai/z-image/turbo/image-to-image
$0.0050 /megapixel
fal.ai
fal/z-image-turbo
Provider Model ID: fal-ai/z-image/turbo
$0.0050 /megapixel
Replicate
replicate/z-image-turbo
Provider Model ID: prunaai/z-image-turbo

Output

Megapixel
$0.0050
Pricing Notes (2)
  • PrunaAI optimized version of Tongyi-MAI Z-Image-Turbo
  • Sub-second generation with 8 steps
View official pricing • As of Jan 02, 2026
Alibaba Cloud
alibaba/z-image-turbo
Provider Model ID: z-image-turbo

Output

Image
$0.015 per image
Image
$0.030 per image
View official pricing • As of Mar 17, 2026

Provider Performance

Fastest generation through replicate at 1,405ms median latency with 89.0% success rate.

Aggregated from real API requests over the last 30 days.

Generation Time

replicate
1,405ms p95: 7,323ms
fal
1,845ms p95: 7,615ms
alibaba
6,836ms p95: 51,551ms

Success Rate

replicate
89.0%
97 / 109 requests
fal
100.0%
45 / 45 requests
alibaba
68.8%
44 / 64 requests

Time to First Byte

replicate
1,399ms
p95: 7,239ms
fal
1,802ms
p95: 7,669ms
alibaba
6,560ms
p95: 51,176ms

Provider Rankings

# Provider p50 Gen Time p95 Gen Time Success Rate TTFB (p50)
1 replicate 1,405ms 7,323ms 89.0% 1,399ms
2 fal 1,845ms 7,615ms 100.0% 1,802ms
3 alibaba 6,836ms 51,551ms 68.8% 6,560ms
Data updated every 15 minutes. Based on all API requests through Lumenfall over the last 30 days.

Z-Image Turbo API OpenAI-compatible

Integrate Z-Image Turbo through Lumenfall’s OpenAI-compatible API to generate images or execute edits using its 6-billion parameter distilled architecture optimized for 8-step inference.

Base URL
https://api.lumenfall.ai/openai/v1
Model
z-image-turbo

Text to Image Generate

Create images from text descriptions

curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/generations \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-image-turbo",
    "prompt": "A serene mountain landscape at sunset",
    "size": "1024x1024"
  }'
# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

Image Editing Edit

Transform existing images with text instructions

curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/edits \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -F "model=z-image-turbo" \
  -F "[email protected]" \
  -F "prompt=Add a starry night sky to this image" \
  -F "size=1024x1024"
# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

Size, Aspect Ratio & Resolution Reference

Three optional parameters for controlling output dimensions

size

Exact pixel dimensions

"1920x1080"
aspect_ratio

Shape only, default scale

"16:9"
resolution

Scale tier, preserves shape

"1K"

Priority when combined

size aspect_ratio + resolution aspect_ratio resolution

size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.

How matching works

Shape matching – we pick the closest supported ratio. Ask for 7:1 on a model with 4:1 and 8:1, you get 8:1.
Scale matching – providers use different tier formats: K tiers (0.5K 1K 2K 4K) or megapixel tiers (0.25 1). If the exact tier isn't available, you get the nearest one.
Dimension clamping – if a model has pixel limits, we clamp dimensions to fit and keep the aspect ratio intact.

Parameters & Unified Output Reference

These work the same regardless of which provider runs your request

response_format

url or b64_json. If you ask for a URL but the provider returns base64, we store it temporarily and hand you a link valid for 60 minutes.

output_format

Pick from png jpeg gif webp avif. We convert if the provider generates a different format.

output_compression

Quality level from 1 to 100 for lossy formats (jpeg, webp, avif). Higher means better quality, larger file.

n

Request multiple images in one call. If the provider caps at 1, we run parallel requests behind the scenes and return them together.

Parameter support

Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:

Mode What happens Example
passthrough Sent as-is to the provider style, quality
renamed Same value, mapped to the field name the provider expects prompt
converted Transformed to the provider's native format size
emulated Works even if the provider has no concept of it n, response_format

Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.

Z-Image Turbo Benchmarks

Alibaba's Z-Image Turbo holds a top 10 position in global text-to-image rankings with a 1253 Elo rating. It remains competitive in high-speed workflows, maintaining a rank of 16 for complex image editing tasks with an Elo of 1021.

Lumenfall Arena
#16
Image Editing
1046 Elo
Lumenfall Arena
#11
Text-to-Image
1251 Elo

Image Editing Landscape

3 without speed data omitted.

Text-to-Image Landscape

13 without speed data omitted.

Competition Results

Text-to-Image

Text Rendering

View leaderboard
#3
Modern Clean Menu
19 models
Text-to-Image
Prompt

“Modern minimalist restaurant menu design, white background with colorful food photos in grid, sections for appetizers/pizza/mains, bold sans-serif fonts, vibrant accents, clean professional layout for casual dining.”

#12
Vintage Cafe Logo
21 models
Text-to-Image
Prompt

“Vintage minimalist restaurant logo for "Caffè Florian", retro cloche dome with steam and "Est. 1720" banner, classic typography, warm brown and cream tones, subtle texture on light background, vector emblem style.”

Image Editing

Photorealism

View leaderboard
Z-Image Turbo edited result for Night Sky Transformation
Original image before Z-Image Turbo editing
Before After
#16
Night Sky Transformation
16 models
Image Editing
Edit instruction

“Change the scene to night: a deep, dark sky with subtle, glistening stars visible behind the mountain.”

Z-Image Turbo edited result for Bald man challenge
Original image before Z-Image Turbo editing
Before After
#15
Bald man challenge
15 models
Image Editing
Edit instruction

“Give the person a full, thick head of natural hair with realistic texture, density, and a natural hairline. Preserve facial features and lighting.”

Text-to-Image

Photorealism

View leaderboard
Text-to-Image
Prompt

“A candid street photo of an elderly Japanese man repairing a red bicycle in light rain, reflections on wet pavement, shallow depth of field, 50mm lens, natural skin texture, imperfect framing, motion blur from passing cars, cinematic but realistic, no stylization.”

Image Editing

Portrait

View leaderboard
Z-Image Turbo edited result for Bald man challenge
Original image before Z-Image Turbo editing
Before After
#15
Bald man challenge
15 models
Image Editing
Edit instruction

“Give the person a full, thick head of natural hair with realistic texture, density, and a natural hairline. Preserve facial features and lighting.”

Text-to-Image

Product, Branding & Commercial

View leaderboard
#12
Vintage Cafe Logo
21 models
Text-to-Image
Prompt

“Vintage minimalist restaurant logo for "Caffè Florian", retro cloche dome with steam and "Est. 1720" banner, classic typography, warm brown and cream tones, subtle texture on light background, vector emblem style.”

Text-to-Image

Portrait

View leaderboard
#9
Fantasy Warrior
21 models
Text-to-Image
Prompt

“Close portrait of a battle-worn paladin in ornate engraved plate armor, hair braided with small beads, faint scars and dirt on the skin, warm torchlight reflecting off metal, shallow depth of field, bokeh sparks, lifelike eyes, highly detailed texture on leather straps and cloth underlayer.”

Uncategorized

Text-to-Image
Prompt

“Hyper-photorealistic scene of fluffy baby animals—a golden retriever puppy, tabby kitten, baby bunny, and red fox kit—with big expressive eyes and ultra-detailed soft fur, playfully chasing butterflies and tumbling together in a lush wildflower meadow, warm golden sunrise light with god rays and dew sparkles, joyful wholesome vibe, 8K masterpiece.”

#8
Geometric Composition
22 models
Text-to-Image
Prompt

“A glass cube on a wooden table. Inside the cube is a small blue sphere. On top of the cube sits a red book. A green plant is behind the cube, partially visible through the glass. Soft window light from the left.”

Text-to-Image
Prompt

“Hyper-photorealistic full-body portrait of a female superhero standing triumphantly on a New York skyscraper rooftop at golden sunset, wearing a classic modest superhero costume with flowing cape, chest emblem, gloves, and boots in red and blue colors, practical design, short hair, strong determined heroic expression looking into the distance, powerful confident stance with hands on hips and cape billowing dramatically in the wind, detailed urban cityscape background, warm natural sunlight with sharp shadows and fabric highlights, ultra-sharp textures on suit, hair, and concrete, 8K masterpiece, empowering family-friendly style.”

Text-to-Image
Prompt

“Hyper-photorealistic interior of a lush Victorian glass greenhouse filled with exotic tropical plants, vibrant blooming orchids, tall ferns, colorful butterflies in flight, sunlight filtering through ornate glass roof creating realistic caustics and dew on leaves, intricate iron framework visible, misty atmosphere, 8K masterpiece.”

Text-to-Image
Prompt

“Create a clear, 45° top-down isometric miniature 3D cartoon scene of Japan's signature dish: sushi, with soft refined textures, realistic PBR materials, gentle lighting, on a small raised diorama base with minimal garnish and plate. Solid light blue background. At top-center: 'JAPAN' in large bold text, 'SUSHI' below it, small flag icon. Perfectly centered, ultra-clean, high-clarity, square format.”

#3
Fantasy Warrior
14 models
Text-to-Image
Prompt

“Close portrait of a battle-worn paladin in ornate engraved plate armor, hair braided with small beads, faint scars and dirt on the skin, warm torchlight reflecting off metal, shallow depth of field, bokeh sparks, lifelike eyes, highly detailed texture on leather straps and cloth underlayer.”

3 attempts – showing best result
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Z-Image Turbo is best for

See all Use Cases

Z-Image Turbo excels in commercial applications, ranking 5th in product and branding with a 55.6% win rate and 7th in portrait generation with a 62.5% win rate. It demonstrates moderate performance in bilingual text rendering but faces significant challenges in specialized photorealism and portrait-specific arena categories.

Z-Image Turbo FAQ

How much does Z-Image Turbo cost?

Z-Image Turbo starts at $0.005 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

How do I use Z-Image Turbo via API?

You can use Z-Image Turbo through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "z-image-turbo". Code examples are available in Python, JavaScript, and cURL.

Which providers offer Z-Image Turbo?

Z-Image Turbo is available through fal.ai, Alibaba Cloud, and Replicate on Lumenfall. Lumenfall automatically routes requests to the best available provider.

What is the maximum resolution for Z-Image Turbo?

Z-Image Turbo supports images up to 2048x2048 resolution.

Overview

Z-Image Turbo is a 6-billion parameter text-to-image model developed by Alibaba’s Tongyi-MAI team. It distinguishes itself by utilizing distillation techniques to enable high-quality image synthesis in eight steps or fewer, making it significantly faster than standard diffusion models. The model is specifically optimized for bilingual text rendering, supporting both Chinese and English characters within generated imagery.

Strengths

  • Inference Latency: By reducing the required sampling steps to a range of 1 to 8, the model provides near-instantaneous image generation suitable for real-time applications.
  • Bilingual Text Rendering: The model excels at accurately rendering complex Chinese characters and English text, a task where many Western-centric models often fail or produce “gibberish.”
  • Visual Fidelity at Low Step Counts: Despite the aggressive distillation for speed, the model maintains high structural integrity and aesthetic consistency that typically requires 25-50 steps in non-distilled models.
  • Multimodal Input Support: It can process both text prompts and image-based references (image-to-image) to guide the generation process, offering flexibility beyond simple text descriptors.

Limitations

  • Fine Detail Saturation: While excellent for rapid generation, the model may lack the extreme micro-detail or complex texture depth found in larger, 12B+ parameter models that utilize longer sampling chains.
  • Step Count Sensitivity: Moving beyond the 8-step threshold does not necessarily improve quality and can sometimes lead to visual artifacts, as the model is strictly tuned for low-step schedules.
  • Stylistic Range: Compared to broader foundation models, the output may lean toward a specific “polished” aesthetic favored by its distillation process, which might require more aggressive prompting to deviate from.

Technical Background

Z-Image Turbo is part of the Z-Image model family and utilizes a distilled architecture derived from a larger latent diffusion framework. To achieve its speed, the developers employed a consistency-based distillation approach that maps the probability flow of the original model into a single or few-step inference trajectory. The integration of a specialized text encoder allows the model to handle bilingual tokens more effectively than models trained solely on English datasets.

Best For

This model is ideal for interactive applications such as live drawing assistants, rapid prototyping for UI/UX design, and social media content creation where speed is prioritized over granular control. It is also a leading choice for projects requiring accurate Chinese typography within images. Z-Image Turbo is available for integration and testing through Lumenfall’s unified API and interactive playground.

Try Z-Image Turbo in Playground

Generate images with custom prompts — no API key needed.

Open Playground