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SPECIFICTION
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SD.Next

github.com

Free plan WebWindowsmacOSLinuxAPISelf-hosted
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Spec score 8.9 #13 of 124 in AI image generators

What it is

SD.Next is an open-source server application and web interface for generating, editing, captioning, upscaling and processing AI images and videos. Workflows include text-to-image, image-to-image, text-to-video, image-to-video, inpainting and outpainting, with PNG and JPG output. The project supports dozens of models and can automatically download selected reference models. Guidance features include LoRA, ControlNet, IPAdapters and Prompt Enhance. Image processing tools cover captioning, tagging, upscaling, interpolation, colorization, filtering and color correction. SDNQ quantization is described as reducing VRAM use by up to 4x; Balanced Offload balances CPU and GPU memory for larger models on limited hardware. Listed hardware options include CUDA, ROCm, ZLUDA, Intel IPEX XPU, OpenVINO, DirectML, Apple M1/M2 MPS, ONNX/Olive and CPU-only execution. SD.Next runs on Linux, macOS and Windows, and provides API access. The project describes desktop and mobile interfaces and localization in about 15 languages. Its security policy says it does not send or share data externally, track user or system data, store inputs or results, or use analytics services. The repository identifies Apache-2.0 as its license.

Spec sheet

Purpose
SD.Next is an open-source server application and web interface for AI image and video generation, captioning, and processing.Read 12 Oct 2026 · github.com
Intended users
The README describes the application as suitable for artists, researchers, and AI enthusiasts.Read 12 Oct 2026 · github.com
Platforms
The README lists Windows, Linux, and macOS support, with GPU acceleration options and CPU-only execution.Read 12 Oct 2026 · github.com
Privacy
The security policy says the app does not send or share data externally, track user or system data, store user inputs or detection results, or use analytics services.Read 12 Oct 2026 · github.com
Support
The README directs users to documentation, Discord, GitHub issues, and discussions for help.Read 12 Oct 2026 · github.com
License
The GitHub repository identifies Apache-2.0 as the project license.Read 12 Oct 2026 · github.com
API access
YesRead 20 Sep 2026 · github.com
Captioning and tagging
The project describes captioning and enhancement with 25+ built-in LLM and VLM models, plus OpenCLIP, WaifuDiffusion, and DeepDanbooru support.Read 12 Oct 2026 · github.com
Extensions
The project supports custom scripts and extensions.Read 12 Oct 2026 · github.com
External connections
The security policy says connections may be made for indexes, installation and upgrade packages, enabled extensions, user-requested model downloads from CivitAI or Hugging Face, and user-submitted benchmark information.Read 12 Oct 2026 · github.com
Guidance tools
The project lists LoRA, ControlNet, IPAdapters, and Prompt Enhance among its guidance features.Read 12 Oct 2026 · github.com
Hardware support
The project lists CUDA, ROCm, ZLUDA, Intel IPEX XPU, OpenVINO, DirectML, Apple M1/M2 MPS, ONNX/Olive, and CPU-only execution support.Read 12 Oct 2026 · vladmandic.github.io
Image editing
YesRead 20 Sep 2026 · github.com
Image processing
Image processing tools include captioning, tagging, upscaling, interpolation, colorization, filtering, and color grading.Read 12 Oct 2026 · github.com
Installation
The project provides installation instructions and quick-start scripts for Linux and Mac, Windows batch files, and PowerShell.Read 12 Oct 2026 · vladmandic.github.io
Interface
The project describes desktop and mobile interfaces and localization in about 15 languages.Read 12 Oct 2026 · github.com
Memory features
SDNQ quantization is described as reducing VRAM use by up to 4x, and Balanced Offload balances CPU and GPU memory for larger models on limited hardware.Read 12 Oct 2026 · vladmandic.github.io
Memory optimization
Its SDNQ quantization engine can reduce VRAM use by up to 4x, and Balanced Offload balances CPU and GPU memory.Read 12 Oct 2026 · github.com
Model support
SD.Next supports a broad range of diffusion models and can automatically download selected reference models.Read 12 Oct 2026 · github.com
Models
The project says it supports dozens of advanced models and can automatically download selected reference models.Read 12 Oct 2026 · vladmandic.github.io
Output formats
PNG,JPGRead 20 Sep 2026 · github.com
Reference images
YesRead 20 Sep 2026 · github.com
Security practices
The security policy says code and included dependencies are automatically scanned for known vulnerabilities and commits are validated before merging.Read 12 Oct 2026 · github.com
Text-to-image
YesRead 20 Sep 2026 · github.com
Workflows
It supports text-to-image, image-to-image, text-to-video, image-to-video, inpainting, outpainting, and upscaling workflows.Read 12 Oct 2026 · github.com

Plans and prices

SD.Next Free Open-source server application and web interface Read 12 Oct 2026 · github.com

Every SD.Next plan and price →

Strong points and limits

Strong points

  • Supports image and video workflows
  • Includes image processing and captioning tools
  • Offers multiple hardware backends
  • API access is available
  • Free and licensed under Apache-2.0

Limits

  • Extensions can be downloaded when enabled
  • Some external connections occur for downloads and updates
  • No hosted service is listed

Who it suits

SD.Next is described as suitable for artists, researchers and AI enthusiasts. Its self-hosted server and varied hardware support may suit users who want to run image and video workflows on their own systems.

Verdict

SD.Next covers image and video generation as well as processing, with multiple model and hardware options. Users should review its installation requirements and understand the external connections described for downloads, updates and enabled extensions.

Where Specifiction places it

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