Stable Diffusion Online

SDXL Online - Free Stable Diffusion XL Playground

Experience the next generation of Stable Diffusion with the Stable Diffusion Web SDXL playground. Produce larger, sharper images with richer colors, better scene composition, and more accurate text rendering-all in your browser with no login required. Try the SDXL image generator demo completely free.

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Ready whenever you are. Tweak your prompt or add references for the best results.

Output Gallery

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Enter your prompt and unleash the power

Why choose SDXL?

  • Two-stage architecture delivers higher fidelity than Stable Diffusion 1.5.
  • Improved prompt understanding with more natural lighting and depth.
  • Larger 1024×1024 native resolution retains fine textures and typography.

Get started fast

  • Enter a detailed prompt and click generate-no code or installs required.
  • Switch between SDXL and other models from the same interface.
  • Use our prompt library for inspiration.

Demand can create a short processing queue. If a generation times out, simply retry-your prompts remain available for the next request.

Where SDXL shines

Premium product renders with SDXL

Generate hero shots for ecommerce, ads, and packaging with SDXL realistic reflections and SDXL studio lighting.

Cinematic storytelling with SDXL

Build world-class concept art, matte paintings, and storyboards with SDXL that capture complex SDXL lighting and depth.

Brand & typography work with SDXL

SDXL improves legibility of logos and display text, making SDXL perfect for branded social assets.

Quick prompting tips

  • Keep prompts between 40-80 words-SDXL thrives on descriptive language without becoming incoherent.
  • Include camera and lens terminology (e.g., “35mm, bokeh, f/1.4”) to control focus and perspective.
  • Use negative prompts like “blur, watermark, low detail” combined with a guidance scale between 7 and 9 for crisp outputs.

Frequently asked questions about SDXL

What is Stable Diffusion XL (SDXL)?
Stable Diffusion XL (SDXL) is an advanced text-to-image AI model released in July 2023 that generates high-quality images at 1024x1024 resolution. It features a 3.5 billion parameter base model with significantly improved image quality, better prompt understanding, and enhanced photorealism compared to previous Stable Diffusion versions. SDXL represents a major leap forward in AI image generation technology.
What are the key improvements in SDXL over SD 1.5?
SDXL offers several major improvements over SD 1.5: a 3x larger UNet backbone with 3.5 billion parameters (compared to 890 million in SD 1.5), dual text encoders for better prompt understanding, native 1024x1024 resolution output, improved photorealism and detail, better handling of hands and anatomy, enhanced text generation within images, and the ability to create high-quality images from simple prompts without extensive keyword stacking.
How does SDXL's dual text encoder system work?
SDXL utilizes two CLIP text encoders working in tandem, including OpenCLIP ViT-G/14, one of the largest OpenCLIP models trained to date. This dual encoder system provides a larger cross-attention context and significantly improves the model's ability to understand and interpret complex text prompts more accurately. The dual text encoders allow it to better capture nuanced descriptions and produce images that more faithfully match user intent.
What is the difference between SDXL Turbo and SDXL Base?
SDXL Turbo is a distilled version of SDXL 1.0 optimized for speed using Adversarial Diffusion Distillation (ADD). Key differences: Turbo generates images in 1-4 steps versus 25-50 steps for base, produces 512x512 images optimally while base targets 1024x1024, generates images in under 1 second on modern GPUs, and doesn't use guidance scale or negative prompts. Turbo trades some quality and resolution for dramatically faster generation speeds.
What image resolution and quality does SDXL produce?
SDXL generates images at native 1024x1024 resolution, a significant upgrade from the 512x512 resolution of SD 1.5. The model produces highly detailed, photorealistic images with improved color accuracy, better composition, enhanced textures, and superior handling of complex scenes. It was trained on multiple aspect ratios, making it versatile for different image compositions while maintaining exceptional quality across various styles from photorealism to artistic interpretations.
What are the hardware requirements for running SDXL?
SDXL requires more powerful hardware than previous Stable Diffusion versions. Minimum: 8GB VRAM GPU (RTX 20XX series or equivalent). Recommended: 12GB VRAM for comfortable use with the refiner model, generating 1024x1024 images in about 20 seconds. Optimal: 16GB+ VRAM for batch generation and faster processing. For fine-tuning and LoRA training: 24GB VRAM recommended. Lower VRAM setups (4-6GB) can work with optimizations like ComfyUI and Tiled VAE, but expect slower generation times.
What are the best practices for writing SDXL prompts?
SDXL excels with natural language descriptions, so be specific and detailed about your desired image. Key practices: describe the subject clearly and position important elements early in the prompt, use comma separation for different concepts, include style specifications and mood descriptors, add technical details like lighting and composition for realism, leverage photography terms (depth of field, camera angles) for photorealistic images, keep negative prompts minimal (needs less negative prompting), and use weight adjustments sparingly as it is more sensitive to keyword emphasis.
Does SDXL support fine-tuning and LoRA training?
Yes, SDXL fully supports fine-tuning methods including LoRA (Low-Rank Adaptation), DreamBooth, and Textual Inversion. LoRA training is efficient, requiring only 5-6 images and 10-15 minutes of training time on suitable hardware. LoRA models are typically 2MB-500MB in size, making them easy to share and use. Multiple platforms like Hugging Face Diffusers, Replicate, and AutoTrain Advance provide tools for fine-tuning, enabling personalized image generation and custom style creation.
What is the SDXL Refiner model and when should I use it?
The SDXL Refiner is a specialized model designed for the final denoising steps to enhance image quality and add fine details. It processes the noisy latents from the base model to produce higher-fidelity results. Use the refiner in two ways: Ensemble of Expert Denoisers (faster, base and refiner work together) or Sequential Refinement (base generates complete image, then refiner enhances it). Best practices: use low refiner strength, apply to noisy images, and avoid using with fine-tuned models as styles may conflict.
Can I use SDXL for commercial purposes?
Yes, SDXL 1.0 Base is available for commercial use under the Stability AI Community License. If your annual revenue is below $1 million USD, you can use it freely for commercial products and services at no cost. Organizations with annual revenues exceeding $1 million USD need to obtain an Enterprise license from Stability AI. Images generated can be used commercially within these licensing terms. Note: Turbo has more restrictive non-commercial research licensing.
How does SDXL compare to Stable Diffusion 3 (SD3)?
SD3 uses a newer diffusion transformer architecture while SDXL uses an enhanced UNet architecture. SD3 generally offers better prompt adherence, more intricate details, and superior text generation in images. However, SDXL remains highly competitive with advantages in cost-effectiveness (10x cheaper to run), a mature SDXL ecosystem with thousands of LoRAs and custom models, excellent results for artistic styles after fine-tuning, and better color gradients and nuanced blends. For most practical applications, SDXL provides an excellent balance of quality and efficiency.
What is SDXL's ensemble of experts architecture?
SDXL employs an ensemble of experts pipeline consisting of two specialized models working together. The base model generates initial latent images with detailed composition and structure, then the refiner model processes these latents through final denoising steps to enhance visual fidelity and add fine details. This two-stage approach allows each model to specialize in different aspects of image generation, resulting in higher quality outputs than single-model approaches while maintaining efficiency.
How fast is SDXL image generation?
Generation speed depends on hardware and settings. On recommended hardware (12GB VRAM), expect approximately 20 seconds per 1024x1024 image with the refiner. With 16GB+ VRAM, generation can be faster, especially for batch processing. On 24GB VRAM GPUs, single images generate in just a few seconds. Turbo variant generates 512x512 images in under 1 second on high-end GPUs (207ms on A100). Lower VRAM configurations (8GB or less) may take several minutes per image depending on optimizations used.
What training data was SDXL trained on?
SDXL was trained on a large-scale dataset including high-resolution images with associated text descriptions. While specific dataset details vary, it leveraged improved training techniques with multi-aspect ratio training, allowing it to handle various image compositions naturally. The model was trained with significantly more compute and data compared to SD 1.5, contributing to its enhanced understanding of complex prompts, improved photorealism, and better handling of challenging concepts like human anatomy and text rendering.
Can SDXL generate text within images?
Yes, SDXL significantly improved text generation capabilities compared to earlier Stable Diffusion versions. While not perfect, it can render legible text within images more reliably than SD 1.5. For best results when generating text, be specific about the text content in your prompt, use quotes around the desired text, mention the style or font if relevant, and specify placement. Complex or very long text strings may still present challenges, but it represents a major advancement in AI text rendering capabilities.