Stable Diffusion WebUI Forge vs Automatic1111: Linux VRAM Usage and Speed Compared

For years, Automatic1111 has served as the de facto standard web interface for Stable Diffusion experimentation. However, as model architectures grew from SD 1.5 (1.8 GB) to SDXL (6.6 GB) and FLUX (12 GB+), Automatic1111 began triggering Out of Memory (OOM) errors on 8GB VRAM graphics cards. SD WebUI Forge was engineered as a direct drop-in replacement with an overhauled backend memory management system.

In this benchmark, we pit Stable Diffusion WebUI Forge against Automatic1111 on Ubuntu 24.04 LTS to determine real-world VRAM savings, batch throughput, and overall stability.

Direct Answer: Which WebUI Should You Choose on Linux?

Choose SD WebUI Forge if you operate an NVIDIA GPU with 8GB or 12GB of VRAM and plan to generate images with SDXL or FLUX. Forge reduces peak VRAM allocation by 35 to 45 percent and improves generation speed by approximately 20 percent on mid-tier hardware. Choose Automatic1111 only if your workflow depends strictly on niche legacy extensions that have not yet ported to Forge.

Architecture Differences: How Forge Optimizes Linux Memory

Automatic1111 keeps checkpoints, text encoders, and VAE decoders resident in GPU VRAM simultaneously. In contrast, Forge utilizes dynamic sub-module streaming (similar to ComfyUI's memory manager), swapping components between system RAM and GPU memory only during the precise inference phase they are needed.

Benchmark Methodology

Both applications were tested under identical Linux conditions on Ubuntu 24.04 LTS:

• Model Checkpoint: SDXL Base 1.0 (fp16, 6.46 GB)
• Resolution: 1024 x 1024 pixels
• Sampler: DPM++ 2M Karras, 30 steps, CFG Scale 7.0
• Hardware: NVIDIA GeForce RTX 3070 (8GB VRAM), 32GB DDR4 System RAM

Benchmark Results Comparison Table

Quick Install: Setting Up Forge on Ubuntu

# Clone repository
git clone https://github.com/lllyasviel/stable-diffusion-webui-forge.git
cd stable-diffusion-webui-forge

# Create environment and run launcher
python3 -m venv venv
./webui.sh

Summary Verdict

For Linux users running local image generation on workstations with 8GB to 16GB of VRAM, SD WebUI Forge is decisively superior. It eliminates out-of-memory crashes on SDXL while maintaining the familiar Automatic1111 UI layout and API compatibility.

For more hands-on benchmarks, check our comparison of Ollama vs vLLM Memory & Latency on Linux and our guide on Running ComfyUI on Ubuntu with NVIDIA Acceleration.