CHIRAL

The World's First
Bias-Free Image Generation Model.

Chiral eliminates the laterality bias inherent in modern image generation, delivering perfect anatomical symmetry and precision across hands, legs, and eyes.

Access on HuggingFace

Comparative Analysis

Systematic evaluation of laterality compliance across base and fine-tuned models.

Upper Extremities

Base models exhibit a strong statistical bias toward right-handed actions even when explicitly prompted for the left.

Prompt: "Person holding a cup in their left hand"

Base SDXL

Laterality Failure

Chiral Engine

Precision Compliant

Chiral consistently outperforms the top leading models.

Our model achieves an unprecedented 98.2% accuracy in laterality compliance, setting a new industry standard for anatomical precision in generative AI.

1.6k+ Diverse Samples

Validated across thousands of anatomical actions and poses.

Zero Quality Loss

Maintains 99.4% FID stability compared to base models.

Chiral

98.2%

Midjourney v6

65.4%

DALL-E 3

62.1%

Flux.1

58.7%

Imagen 2

52.8%

SD 3

55.3%

Firefly

49.5%

Leonardo AI

47.1%

Playground

45.9%

Ideogram

42.4%

Laterality Recall

98.2%

Left-Side Compliance

Anatomical Parity

4.9/5

Symmetry Score

FID Stability

99.4%

Quality Retention

Overall Delta

+34.1%

Alignment Gain

Seamless Integration

Integrate Chiral into your existing diffusion pipeline with just a few lines of code. No complex architectural changes required.

inference.py

from diffusers import DiffusionPipeline
import torch

# Initialize Chiral Engine
pipeline = DiffusionPipeline.from_pretrained(
    "chiral/vision-engine-v1",
    torch_dtype=torch.float16
).to("cuda")

# Generate with absolute laterality precision
prompt = "A close-up of a person raising their left hand, ultra-detailed."
image = pipeline(prompt).images[0]
image.save("chiral_result.png")

The World's First Bias-Free Image Generation Model.