baidu/ERNIE-Image-Turbo API & Inference Endpoint

Released Versions

ERNIE-Image: Our SFT model, delivers stronger general-purpose capability and instruction fidelity in typically 50 inference steps.

ERNIE-Image-Turbo: Our Turbo model, optimized by DMD and RL, achieves faster speed and higher aesthetics in only 8 inference steps.

Benchmark

GENEval

Table with columns: Model, Single Object, Two Object, Counting, Colors, Position, Attribute Binding, Overall
Model	Single Object	Two Object	Counting	Colors	Position	Attribute Binding	Overall
ERNIE-Image (w/o PE)	1.0000	0.9596	0.7781	0.9282	0.8550	0.7925	0.8856
ERNIE-Image (w/ PE)	0.9906	0.9596	0.8187	0.8830	0.8625	0.7225	0.8728
Qwen-Image	0.9900	0.9200	0.8900	0.8800	0.7600	0.7700	0.8683
ERNIE-Image-Turbo (w/o PE)	1.0000	0.9621	0.7906	0.9202	0.7975	0.7300	0.8667
ERNIE-Image-Turbo (w/ PE)	0.9938	0.9419	0.8375	0.8351	0.7950	0.7025	0.8510
FLUX.2-klein-9B	0.9313	0.9571	0.8281	0.9149	0.7175	0.7400	0.8481
Z-Image	1.0000	0.9400	0.7800	0.9300	0.6200	0.7700	0.8400
Z-Image-Turbo	1.0000	0.9500	0.7700	0.8900	0.6500	0.6800	0.8233

OneIG-EN

Table with columns: Model, Alignment, Text, Reasoning, Style, Diversity, Overall
Model	Alignment	Text	Reasoning	Style	Diversity	Overall
Nano Banana 2.0	0.8880	0.9440	0.3340	0.4810	0.2450	0.5780
Seedream 4.5	0.8910	0.9980	0.3500	0.4340	0.2070

OneIG-ZH

Table with columns: Model, Alignment, Text, Reasoning, Style, Diversity, Overall
Model	Alignment	Text	Reasoning	Style	Diversity	Overall
Nano Banana 2.0	0.8430	0.9830	0.3110	0.4610	0.2360	0.5670
ERNIE-Image (w/ PE)	0.8299	0.9539	0.3056	0.4342	0.2478

LongTextBench

Table with columns: Model, LongText-Bench-EN, LongText-Bench-ZH, Avg
Model	LongText-Bench-EN	LongText-Bench-ZH	Avg
Seedream 4.5	0.9890	0.9873	0.9882
ERNIE-Image (w/ PE)	0.9804	0.9661	0.9733
GLM-Image	0.9524	0.9788	0.9656
ERNIE-Image-Turbo (w/ PE)	0.9675	0.9636	0.9655

Quick Start

Recommended Parameters

Resolution:
- 1024x1024
- 848x1264
- 1264x848
- 768x1376
- 896x1200
- 1376x768
- 1200x896
Guidance scale: 1.0
Inference steps: 8

Diffusers

Install the latest version of diffusers:

markdown
pip install git+https://github.com/huggingface/diffusers

python
import torch
from diffusers import ErnieImagePipeline

pipe = ErnieImagePipeline.from_pretrained(
    "Baidu/ERNIE-Image-Turbo",
    torch_dtype=torch.bfloat16,
).to("cuda")

image = pipe(
    prompt="This is a photograph depicting an urban street scene. Shot at eye level, it shows a covered pedestrian or commercial street. Slightly below the center of the frame, a cyclist rides away from the camera toward the background, appearing as a dark silhouette against backlighting with indistinct details. The ground is paved with regular square tiles, bisected by a prominent tactile paving strip running through the scene, whose raised textures are clearly visible under the light. Light streams in diagonally from the right side of the frame, creating a strong backlight effect with a distinct Tyndall effect—visible light beams illuminating dust or vapor in the air and casting long shadows across the street. Several pedestrians appear on the left side and in the distance, some with their backs to the camera and others walking sideways, all rendered as silhouettes or semi-silhouettes. The overall color palette is warm, dominated by golden yellows and dark browns, evoking the atmosphere of dusk or early morning.",
    height=1264,
    width=848,
    num_inference_steps=8,
    guidance_scale=1.0,
    use_pe=True # use prompt enhancer
).images[0]

image.save("output.png")

SGLang

Install the latest version of sglang:

markdown
git clone https://github.com/sgl-project/sglang.git

Start the server:

bash
sglang serve --model-path baidu/ERNIE-Image-Turbo

Send a generation request:

bash
curl -X POST http://localhost:30000/v1/images/generations \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "This is a photograph depicting an urban street scene. Shot at eye level, it shows a covered pedestrian or commercial street. Slightly below the center of the frame, a cyclist rides away from the camera toward the background, appearing as a dark silhouette against backlighting with indistinct details. The ground is paved with regular square tiles, bisected by a prominent tactile paving strip running through the scene, whose raised textures are clearly visible under the light. Light streams in diagonally from the right side of the frame, creating a strong backlight effect with a distinct Tyndall effect—visible light beams illuminating dust or vapor in the air and casting long shadows across the street. Several pedestrians appear on the left side and in the distance, some with their backs to the camera and others walking sideways, all rendered as silhouettes or semi-silhouettes. The overall color palette is warm, dominated by golden yellows and dark browns, evoking the atmosphere of dusk or early morning.",
    "height": 1264,
    "width": 848,
    "num_inference_steps": 8,
    "guidance_scale": 1.0,
    "use_pe": true
  }' \
  --output output.png

Model

Single Object

Two Object

Counting

Colors

Position

Attribute Binding

Overall

ERNIE-Image (w/o PE)

1.0000

0.9596

0.7781

0.9282

0.8550

0.7925

0.8856

ERNIE-Image (w/ PE)

0.9906

0.9596

0.8187

0.8830

0.8625

0.7225

0.8728

Qwen-Image

0.9900

0.9200

0.8900

0.8800

0.7600

0.7700

0.8683

ERNIE-Image-Turbo (w/o PE)

1.0000

0.9621

0.7906

0.9202

0.7975

0.7300

0.8667

ERNIE-Image-Turbo (w/ PE)

0.9938

0.9419

0.8375

0.8351

0.7950

0.7025

0.8510

FLUX.2-klein-9B

0.9313

0.9571

0.8281

0.9149

0.7175

0.7400

0.8481

Z-Image

1.0000

0.9400

0.7800

0.9300

0.6200

0.7700

0.8400

Z-Image-Turbo

1.0000

0.9500

0.7700

0.8900

0.6500

0.6800

0.8233

Model

Alignment

Text

Reasoning

Style

Diversity

Overall

Nano Banana 2.0

0.8880

0.9440

0.3340

0.4810

0.2450

0.5780

Seedream 4.5

0.8910

0.9980

0.3500

0.4340

0.2070

Model

Alignment

Text

Reasoning

Style

Diversity

Overall

Nano Banana 2.0

0.8430

0.9830

0.3110

0.4610

0.2360

0.5670

ERNIE-Image (w/ PE)

0.8299

0.9539

0.3056

0.4342

0.2478

Model

LongText-Bench-EN

LongText-Bench-ZH

Avg

Seedream 4.5

0.9890

0.9873

0.9882

ERNIE-Image (w/ PE)

0.9804

0.9661

0.9733

GLM-Image

0.9524

0.9788

0.9656

ERNIE-Image-Turbo (w/ PE)

0.9675

0.9636

0.9655

python

import torch
from diffusers import ErnieImagePipeline

pipe = ErnieImagePipeline.from_pretrained(
    "Baidu/ERNIE-Image-Turbo",
    torch_dtype=torch.bfloat16,
).to("cuda")

image = pipe(
    prompt="This is a photograph depicting an urban street scene. Shot at eye level, it shows a covered pedestrian or commercial street. Slightly below the center of the frame, a cyclist rides away from the camera toward the background, appearing as a dark silhouette against backlighting with indistinct details. The ground is paved with regular square tiles, bisected by a prominent tactile paving strip running through the scene, whose raised textures are clearly visible under the light. Light streams in diagonally from the right side of the frame, creating a strong backlight effect with a distinct Tyndall effect—visible light beams illuminating dust or vapor in the air and casting long shadows across the street. Several pedestrians appear on the left side and in the distance, some with their backs to the camera and others walking sideways, all rendered as silhouettes or semi-silhouettes. The overall color palette is warm, dominated by golden yellows and dark browns, evoking the atmosphere of dusk or early morning.",
    height=1264,
    width=848,
    num_inference_steps=8,
    guidance_scale=1.0,
    use_pe=True # use prompt enhancer
).images[0]

image.save("output.png")

bash

curl -X POST http://localhost:30000/v1/images/generations \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "This is a photograph depicting an urban street scene. Shot at eye level, it shows a covered pedestrian or commercial street. Slightly below the center of the frame, a cyclist rides away from the camera toward the background, appearing as a dark silhouette against backlighting with indistinct details. The ground is paved with regular square tiles, bisected by a prominent tactile paving strip running through the scene, whose raised textures are clearly visible under the light. Light streams in diagonally from the right side of the frame, creating a strong backlight effect with a distinct Tyndall effect—visible light beams illuminating dust or vapor in the air and casting long shadows across the street. Several pedestrians appear on the left side and in the distance, some with their backs to the camera and others walking sideways, all rendered as silhouettes or semi-silhouettes. The overall color palette is warm, dominated by golden yellows and dark browns, evoking the atmosphere of dusk or early morning.",
    "height": 1264,
    "width": 848,
    "num_inference_steps": 8,
    "guidance_scale": 1.0,
    "use_pe": true
  }' \
  --output output.png

ERNIE-Image-Turbo

README

Released Versions

Benchmark

GENEval

OneIG-EN

OneIG-ZH

LongTextBench

Quick Start

Recommended Parameters

Diffusers

SGLang

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README

Released Versions

Benchmark

GENEval

OneIG-EN

OneIG-ZH

LongTextBench

Quick Start

Recommended Parameters

Diffusers

SGLang