Hybrid Inference

Empowering local AI builders with Hybrid Inference

Hybrid Inference is an experimental feature. Feedback can be provided here.

Why use Hybrid Inference?

Hybrid Inference offers a fast and simple way to offload local generation requirements.

• 🚀 Reduced Requirements: Access powerful models without expensive hardware.
• 💎 Without Compromise: Achieve the highest quality without sacrificing performance.
• 💰 Cost Effective: It’s free! 🤑
• 🎯 Diverse Use Cases: Fully compatible with Diffusers 🧨 and the wider community.
• 🔧 Developer-Friendly: Simple requests, fast responses.

Available Models

• VAE Decode 🖼️: Quickly decode latent representations into high-quality images without compromising performance or workflow speed.
• VAE Encode 🔢: Efficiently encode images into latent representations for generation and training.
• Text Encoders 📃 (coming soon): Compute text embeddings for your prompts quickly and accurately, ensuring a smooth and high-quality workflow.

Integrations

• SD.Next: All-in-one UI with direct supports Hybrid Inference.
• ComfyUI-HFRemoteVae: ComfyUI node for Hybrid Inference.

Changelog

• March 10 2025: Added VAE encode
• March 2 2025: Initial release with VAE decoding

Contents

The documentation is organized into three sections:

• VAE Decode Learn the basics of how to use VAE Decode with Hybrid Inference.
• VAE Encode Learn the basics of how to use VAE Encode with Hybrid Inference.
• API Reference Dive into task-specific settings and parameters.