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Ultimate SD1.5 Photorealistic Setup Guide: Forge Classic + CyberRealistic

Updated
11 min read
Ultimate SD1.5 Photorealistic Setup Guide: Forge Classic + CyberRealistic

Introduction

  • In late 2025, while the AI image generation community chases cutting-edge models like FLUX.2, Qwen, and Z-Image, Stable Diffusion 1.5 remains remarkably relevant for one specific use case: versatile, high-quality photorealistic generation of people and objects on modest hardware.
  • This guide demonstrates how to combine five carefully selected components—Stable Diffusion WebUI Forge Classic, CyberRealistic v9.0, 4x_NickelbackFS upscaler, and ADetailer—into a cohesive workflow that delivers exceptional results on an RTX 3080 10GB. The setup represents the pinnacle of what SD1.5 can achieve in 2025: not the newest technology, but arguably the most refined for photorealistic human and object rendering.

"I still love using SD1.5. It's like listening to vinyl or cassette tapes: yes, high-resolution digital audio exists, but there's something personal and satisfying about older formats. For me, SD1.5 isn't just nostalgia—it's where I started. My first checkpoint, CyberRealistic, was trained on this."

— u/kaosnews (Cyberdelia, CyberRealistic creator) [11 upvotes]

Why This Stack in 2025?

The Case for SD1.5

AdvantageDescription
Speed2-4 seconds per image on RTX 3080
Low VRAMRuns comfortably on 4GB VRAM
ControlNet MaturityNo model since SD1.5 has achieved equivalent ControlNet ecosystem depth
Checkpoint DiversityThousands of fine-tuned/merged models, continuously updated through 2025
Inpainting ExcellenceStill unmatched for detail correction workflows

The Component Synergy

  • Stable Diffusion WebUI Forge Classic: Stripped-down WebUI optimized exclusively for SD1.5/SDXL—no bloatware
  • CyberRealistic v9.0: The most LoRA-compatible photorealistic checkpoint with exceptional prompt comprehension
  • 4x_NickelbackFS: Detail-preserving upscaler specifically trained on photographic content
  • ADetailer: Automatic face/hand detection and inpainting to fix SD1.5's anatomical weaknesses

Component 1: Forge Classic — The Lightest SD1.5 WebUI

What is Forge Classic?

  • Forge Classic is a community fork of the original Stable Diffusion WebUI Forge, developed by Haoming02. After lllyasviel(the original Forge creator) shifted focus to other projects in late 2024, the community fragmented into multiple forks. Forge Classic took a unique approach: strip everything except SD1.5 and SDXL support to create the fastest, lightest WebUI available.

"Classic mainly serves as an archive for the 'previous' version of Forge, which was built on Gradio 3.41.2 before the major changes were introduced. Additionally, this fork is focused exclusively on SD1.5 and SDXL checkpoints, having various optimizations implemented, with the main goal of being the lightest WebUI without any bloatwares."

— Forge Classic GitHub README

Key Features

FeatureBenefit
SD1.5/SDXL ExclusiveRemoved SD2, Alt-Diffusion, SVD, Z123 code for smaller footprint
~25% Speed BoostVia fp16_accumulation (PyTorch 2.7+) or cublas_ops
~10% Additional SpeedVia SageAttention on RTX 30XX+ GPUs
Persistent LoRA PatchingNo reload between generations—saves ~1 second per image
v-pred SDXL SupportCompatible with NoobAI and similar v-prediction checkpoints
UV Package ManagerDramatically faster dependency installation

Installation

  • Prerequisites:
    • Windows 10/11
    • NVIDIA GPU with CUDA support (RTX 20XX or newer recommended)
    • Git installed
    • Python 3.11.9 (specific version required)

Step 1: Install Python 3.11.9

  • Download from:
# Download Python 3.11.9
https://www.python.org/ftp/python/3.11.9/python-3.11.9-amd64.exe
- During installation:
- Check "Add python.exe to PATH" (bottom checkbox)
- Click "Install Now"

# Verify installation:
PS> where.exe python
C:\Users\{YOUR-USERNAME}\AppData\Local\Programs\Python\Python311\python.exe

Step 2: Clone Forge Classic

PS> git clone https://github.com/Haoming02/sd-webui-forge-classic
PS> cd sd-webui-forge-classic

Step 3: Configure Launch Script

  • Open webui-user.bat in a text editor:
PS> notepad webui-user.bat
  • Replace contents with:
@echo off
set PYTHON=C:\Users\{YOUR-USERNAME}\AppData\Local\Programs\Python\Python311\python.exe
set COMMANDLINE_ARGS=--no-download-sd-model --cuda-malloc --cuda-stream --pin-shared-memory
call webui.bat

Step 4: First Launch

PS> .\webui-user.bat
  • The first launch will download dependencies and set up the environment. This may take 10-20 minutes depending on your internet connection.

Tip: Command Line Arguments Explained

ArgumentPurpose
--no-download-sd-modelPrevents automatic model download; you'll add your own
--cuda-mallocUses CUDA's memory allocator for better GPU memory management
--cuda-streamEnables CUDA streams for parallel operations
--pin-shared-memoryPins shared memory for faster CPU-GPU transfers
  • For RTX 3080 10GB, add --medvram only if you encounter out-of-memory errors during high-resolution generation.

Component 2: CyberRealistic v9.0 — The Checkpoint

What is CyberRealistic?

  • CyberRealistic is a photorealistic checkpoint created by Cyberdelia(kaosnews), one of the most respected model creators in the SD1.5 community. First released in early 2023, it has been continuously refined through version 9.0(released 2025). The model served as a foundation for Realistic Vision, one of the most downloaded SD1.5 checkpoints on Civitai.

"The last version of CyberRealistic amazed me with its ability to accurately understand long prompts. I prefer personal merges, but V9 is a must-have in the SD 1.5 library. We are lucky to have projects like CyberRealistic."

— u/parasang [11 upvotes]

Why CyberRealistic v9.0?

1. Superior Prompt Comprehension

  • SD1.5 models typically struggle with the CLIP tokenizer's 77-token limit and complex prompt interpretation. CyberRealistic v9.0 stands out for its ability to parse and follow detailed prompts accurately.

2. Best-in-Class LoRA Compatibility

"EpicRealism has much better prompt following but is terrible with LoRAs. Realistic Vision isn't that... realistic. CyberRealistic is amazing with LoRAs, though prompt following isn't as good as EpicRealism. I usually use CyberRealistic for realistic photo generation because I combine multiple LoRAs."

— u/BogFrog1682 [4 upvotes]

3. Beginner to Expert Range

"CyberRealistic is tuned for both textual inversion and LoRA, so it's great for anyone from total beginners to hardcore prompt wizards."

— Civitai model description

Download and Installation

# Download
https://civitai.com/models/15003/cyberrealistic
- Select: `cyberrealistic_v90.safetensors`

# Installation: Place the file in:
sd-webui-forge-classic\models\Stable-diffusion\
  • According to Civitai model page:
    • Sampling method: [DPM++ SDE Karras] / [DPM++ 2M Karras]
    • VAE: Already Baked In (None)
    • Sampling steps: 30
    • Resolution: 512x768
    • CFG: 5
    • Upscale: 2x
    • Upscaler: 4x_NickelbackFS_72000_G
    • Denoising strength: 0.3

Tip: CyberRealistic Negative Embedding

  • Cyberdelia provides a companion negative embedding that improves output quality:
# Download
https://civitai.com/models/77976/cyberrealistic-negative

# Installation: Place the file in:
sd-webui-forge-classic\models\embeddings\

# Usage
- Add `CyberRealistic_Negative` to your negative prompt box.

Component 3: 4x_NickelbackFS — The Upscaler

What is 4x_NickelbackFS?

  • 4x_NickelbackFS is an ESRGAN-based upscaler trained specifically on photographic content. It belongs to the Nickelback family of upscalers that prioritize detail preservation over aggressive enhancement.

"This model aims to improve further on what has been achieved by the old Nickelback which was an improvement attempt over 4xESRGAN and also 4xBox. It can upscale most pictures/photos (granted they are clean enough) without destroying as much detail as Box and basic ESRGAN."

— OpenModelDB

Technical Specifications

SpecificationValue
ArchitectureESRGAN
Scale4x
Size64nf23nb
Color ModeRGB
Training DatasetWallpapers
Training Iterations72,000

Why This Upscaler?

    1. Photorealistic Optimization: Trained on high-quality wallpaper images, making it ideal for photorealistic outputs
    1. Detail Preservation: Unlike aggressive upscalers, it maintains original details without adding artificial sharpening
    1. Community Proven: Frequently recommended on r/StableDiffusion for realistic image workflows
    1. Official Recommendation: Listed as the recommended upscaler on CyberRealistic's Civitai page

Download and Installation

# Download
https://openmodeldb.info/models/4x-NickelbackFS

# Installation: Place the `.pth` file in:
sd-webui-forge-classic\models\ESRGAN\

Optimal Hires Fix Settings

  • For CyberRealistic v9.0 with 4x_NickelbackFS:
SettingValueNotes
Upscaler4x_NickelbackFS_72000_GSelect from dropdown
Hires Steps15Sufficient for detail refinement
Denoising Strength0.3Official recommendation; 0.5 introduces composition changes
Upscale by2512x768 → 1024x1536

Tip: Denoising Strength Guidelines

DenoisingEffect
0.25-0.35Preserves composition, adds detail only (recommended)
0.4-0.5Begins modifying image; some elements may change
0.5+Significant changes; result may differ from original

Component 4: ADetailer — The Face/Hand Fixer

What is ADetailer?

  • ADetailer(After Detailer) is an extension that automatically detects faces, hands, and bodies in generated images, then applies targeted inpainting to fix them. It's the primary solution for SD1.5's notorious issues with facial distortion and anatomical errors.

"ADetailer is an extension for the stable diffusion webui that does automatic masking and inpainting. It is similar to the Detection Detailer."

— ADetailer GitHub

Available Detection Models

ModelTargetmAP 50mAP 50-95
face_yolov8n.pt2D/realistic face0.6600.366
face_yolov8s.pt2D/realistic face0.7130.404
hand_yolov8n.pt2D/realistic hand0.7670.505
person_yolov8n-seg.pt2D/realistic person0.7820.555

Installation

# From [Extensions] Tab (Recommended)
1. Open Forge Classic
2. Go to [Extensions] tab
3. Go to [Install from URL] tab
4. Enter: https://github.com/Bing-su/adetailer.git
5. Click [Install]
6. Go to [Installed] tab
7. Click [Apply and restart UI]
8. Restart the Forge Classic completely
SettingValueNotes
ADetailer modelface_yolov8n.ptFast, accurate for realistic faces
ADetailer prompt(leave blank)Uses main prompt
ADetailer negative prompt(leave blank)Uses main negative prompt
Detection confidence0.3Default; lower = more detections
Mask min ratio0.0
Mask max ratio1.0
Inpaint denoising strength0.3-0.4Higher values change face style

Tip: Hand Detection Limitations

  • The hand detection model(hand_yolov8n.pt) is functional but not as refined as face detection. For critical hand accuracy:
      1. Generate multiple images and select the best
      1. Use img2img inpainting for manual correction
      1. Consider hand-specific LoRAs

Complete Workflow: Putting It All Together

Final Settings Summary

  • Checkpoint: [cyberrealistic_v90.safetensors]
  • VAE: [None]
  • Sampling Method: [DPM++ 2M SDE]
  • Sampling Steps: [30]
  • Hires. fix: [Enabled]
  • Upscaler: [4x_NickelbackFS_72000_G]
  • Upscale by: [2]
  • Hires steps: [15]
  • Denoising strength: [0.3]
  • Resolution: [512x768]
  • CFG Scale: [5]
  • ADetailer: [Enabled]
  • ADetailer model: [face_yolov8n.pt]
  • ADetailer denoising: [0.35]
  • Negative Embedding: [CyberRealistic_Negative]

Example Prompts

# Object Example:
# Positive Prompt
(raw photo:1.4),(photorealistic:1.4),(8k uhd:1.4),(magazine pictorial:1.4),(candid photography:1.4),(captured in the moment:1.4),(candid moments:1.4),
(wide angle view:1.4),
(bokeh:1.4),(fujifilm xt3:1.4),(35mm film grain:1.4),(analog film photography:1.4),(vintage editorial style:1.4),(Kodak Portra 800 film:1.4),(lo-fi aesthetic:1.4),
(shallow depth of field:1,4),(sharp focus:1.4),
(natural lighting:1.4),(soft diffused light:1.4),(soft shadows:1.4),
(ultra-detailed:1.4),(skin texture:1.4),(high detailed skin texture:1.4),(detailed skin texture:1.4),(skin pores:1.4),(detailed skin:1.4),(translucent skin:1.4),(alabaster complexion:1.4),
(subsurface scattering:1.4),(subsurface skin scattering:1.4),(realistic epidermal texture:1.4),(microscopic details:1.4),(fine pores:1.4),
(commercial advertisement style:1.4),(refreshing atmosphere:1.4),(lively atmosphere:1.4),(airy feel:1.4),
(extremely bright sunny day:1.4),(blinding mid-day sun:1.4),(clear deep blue sky with fluffy white clouds:1.4),

(full body:1.4), (wide shot:1.4), extreme long shot, a mysterious Inuit person standing alone on a vast snowy field, wearing traditional thick fur parka and leather boots, (neutral expression:1.2), (looking at viewer:1.1), face visibly cold, breathless silence, soft diffused light, whiteout background, negative space

# Negative Prompt
(CyberSuperDuperNeg:1.4),

(close up:1.5), (portrait:1.5), (face focus:1.4), zoom in, smiling, happy, warm colors, bright sun, colorful, cropped, out of frame, multiple people, illustration, painting, 3d, render, cartoon, anime, low quality, worst quality, deformed, blurry

Generation Workflow

    1. Compose Prompt: Write detailed positive/negative prompts
    1. Generate Base Image: 512x768 at 30 steps
    1. ADetailer Pass: Automatic face correction runs
    1. Hires Fix: Upscales to 1024x1536 with detail enhancement
    1. Review and Iterate: Adjust seed or prompt as needed

Performance Expectations

RTX 3080 10GB Benchmarks

  • Based on community reports and Forge Classic documentation:
OperationApproximate Time
Base generation (512x768, 30 steps)~3-5 seconds
ADetailer pass~2-3 seconds
Hires fix (2x upscale, 15 steps)~8-12 seconds
Total per image~15-20 seconds

VRAM Usage

StageApproximate VRAM
Model loaded~4GB
During generation~6-7GB
During Hires fix~8-9GB
Peak~9GB
  • The RTX 3080 10GB has comfortable headroom for this workflow without requiring --medvram.

Advanced Optimizations

SageAttention (Optional)

  • For (())RTX 30XX GPUs(()), SageAttention provides ~10% additional speed:
      1. Install Triton manually (see Forge Classic GitHub for instructions)
      1. Add --sage-attention to command line arguments

Persistent LoRA Patching

  • Enabled by default in Forge Classic. This prevents LoRA reload between generations, saving ~1 second per image when using the same LoRA configuration.

Limitations and Workarounds

Known SD1.5 Limitations

LimitationWorkaround
Hand/finger issuesADetailer + manual inpainting
512px native resolutionAlways use Hires fix
Complex posesMultiple generations + cherry-picking
Text renderingUse ControlNet or external tools

When to Consider Alternatives

  • Need higher native resolution: SDXL with Illustrious/Pony
  • Need latest model architectures: Forge Neo with FLUX/Qwen
  • Need complex node workflows: ComfyUI

References

  • Forge Classic: https://github.com/Haoming02/sd-webui-forge-classic
  • ADetailer: https://github.com/Bing-su/adetailer
  • CyberRealistic: https://civitai.com/models/15003/cyberrealistic
  • CyberRealistic Discord: https://discord.gg/GUByyMuua3
  • CyberRealistic Prompt Helper (ChatGPT): https://chatgpt.com/g/g-6834133e3ab881918a91b3ec6b9eb01f-cyberrealistic-prompt-helper
  • CyberRealistic Negative: https://civitai.com/models/77976/cyberrealistic-negative
  • 4x_NickelbackFS: https://openmodeldb.info/models/4x-NickelbackFS
  • r/StableDiffusion Forge abandonment discussion: https://www.reddit.com/r/StableDiffusion/comments/1h5jdmz/has_forge_been_abandoned/
  • SD1.5 in 2025: https://www.reddit.com/r/StableDiffusion/comments/1lyw8rm/
  • Best SD1.5 checkpoints: https://www.reddit.com/r/StableDiffusion/comments/1jbiw3x/

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Taehyeong Lee | Software Engineer

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I am Software Engineer with 15 years of experience, working at Gentle Monster. I specialize in developing high-load, large-scale processing APIs using Kotlin and Spring Boot. I live in Seoul, Korea.