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_NickelbackFSupscaler, andADetailer—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
| Advantage | Description |
| Speed | 2-4 seconds per image on RTX 3080 |
| Low VRAM | Runs comfortably on 4GB VRAM |
| ControlNet Maturity | No model since SD1.5 has achieved equivalent ControlNet ecosystem depth |
| Checkpoint Diversity | Thousands of fine-tuned/merged models, continuously updated through 2025 |
| Inpainting Excellence | Still 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 Classicis 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
| Feature | Benefit |
| SD1.5/SDXL Exclusive | Removed SD2, Alt-Diffusion, SVD, Z123 code for smaller footprint |
| ~25% Speed Boost | Via fp16_accumulation (PyTorch 2.7+) or cublas_ops |
| ~10% Additional Speed | Via SageAttention on RTX 30XX+ GPUs |
| Persistent LoRA Patching | No reload between generations—saves ~1 second per image |
| v-pred SDXL Support | Compatible with NoobAI and similar v-prediction checkpoints |
| UV Package Manager | Dramatically 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.batin 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
| Argument | Purpose |
--no-download-sd-model | Prevents automatic model download; you'll add your own |
--cuda-malloc | Uses CUDA's memory allocator for better GPU memory management |
--cuda-stream | Enables CUDA streams for parallel operations |
--pin-shared-memory | Pins shared memory for faster CPU-GPU transfers |
- For RTX 3080 10GB, add
--medvramonly if you encounter out-of-memory errors during high-resolution generation.
Component 2: CyberRealistic v9.0 — The Checkpoint
What is CyberRealistic?
CyberRealisticis 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\
Official Recommended Settings
- 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_NickelbackFSis 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
| Specification | Value |
| Architecture | ESRGAN |
| Scale | 4x |
| Size | 64nf23nb |
| Color Mode | RGB |
| Training Dataset | Wallpapers |
| Training Iterations | 72,000 |
Why This Upscaler?
- Photorealistic Optimization: Trained on high-quality wallpaper images, making it ideal for photorealistic outputs
- Detail Preservation: Unlike aggressive upscalers, it maintains original details without adding artificial sharpening
- Community Proven: Frequently recommended on r/StableDiffusion for realistic image workflows
- 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:
| Setting | Value | Notes |
| Upscaler | 4x_NickelbackFS_72000_G | Select from dropdown |
| Hires Steps | 15 | Sufficient for detail refinement |
| Denoising Strength | 0.3 | Official recommendation; 0.5 introduces composition changes |
| Upscale by | 2 | 512x768 → 1024x1536 |
Tip: Denoising Strength Guidelines
| Denoising | Effect |
| 0.25-0.35 | Preserves composition, adds detail only (recommended) |
| 0.4-0.5 | Begins 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
| Model | Target | mAP 50 | mAP 50-95 |
| face_yolov8n.pt | 2D/realistic face | 0.660 | 0.366 |
| face_yolov8s.pt | 2D/realistic face | 0.713 | 0.404 |
| hand_yolov8n.pt | 2D/realistic hand | 0.767 | 0.505 |
| person_yolov8n-seg.pt | 2D/realistic person | 0.782 | 0.555 |
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
Recommended Settings for Photorealistic Output
| Setting | Value | Notes |
| ADetailer model | face_yolov8n.pt | Fast, accurate for realistic faces |
| ADetailer prompt | (leave blank) | Uses main prompt |
| ADetailer negative prompt | (leave blank) | Uses main negative prompt |
| Detection confidence | 0.3 | Default; lower = more detections |
| Mask min ratio | 0.0 | |
| Mask max ratio | 1.0 | |
| Inpaint denoising strength | 0.3-0.4 | Higher 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:- Generate multiple images and select the best
- Use img2img inpainting for manual correction
- 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
- Compose Prompt: Write detailed positive/negative prompts
- Generate Base Image: 512x768 at 30 steps
- ADetailer Pass: Automatic face correction runs
- Hires Fix: Upscales to 1024x1536 with detail enhancement
- Review and Iterate: Adjust seed or prompt as needed
Performance Expectations
RTX 3080 10GB Benchmarks
- Based on community reports and Forge Classic documentation:
| Operation | Approximate 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
| Stage | Approximate 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:
- Install Triton manually (see Forge Classic GitHub for instructions)
- Add
--sage-attentionto command line arguments
- Add
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
| Limitation | Workaround |
| Hand/finger issues | ADetailer + manual inpainting |
| 512px native resolution | Always use Hires fix |
| Complex poses | Multiple generations + cherry-picking |
| Text rendering | Use 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/




