for Stable Diffusion / SDXL / Flux UI
TL;DR
ComfyUI is the fastest and most memory-efficient for SDXL and Flux, while Automatic1111 offers the broadest feature set and community extensions. Forge is a performance-focused fork of A1111 that competes with ComfyUI on speed but lags slightly in Flux support.
ComfyUI wins for Stable Diffusion / SDXL / Flux UI. ComfyUI is the fastest and most memory-efficient for SDXL and Flux, while Automatic1111 offers the broadest feature set and community extensions. Forge is a performance-focused fork of A1111 that competes with ComfyUI on speed but lags slightly in Flux support.
Winner: Inference Speed (SDXL 1024x1024, RTX 4090, 50 steps)
ComfyUI
Winner: Inference Speed (Flux.1 Dev 1024x1024, 50 steps)
ComfyUI
Winner: VRAM Usage (SDXL, batch size 1)
ComfyUI
Overall Pick
ComfyUI
| Specification | ComfyUI | AUTOMATIC1111 |
|---|---|---|
| Inference Speed (SDXL 1024x1024, RTX 4090, 50 steps) | 7.2 s | 9.1 s |
| Inference Speed (Flux.1 Dev 1024x1024, 50 steps) | 14.5 s | 19.8 s |
| VRAM Usage (SDXL, batch size 1) | 3.2 GB | 4.0 GB |
| VRAM Usage (Flux, fp16, no TAEF1) | 5.8 GB | 7.1 GB |
| Low VRAM Mode (4 GB cards) | Yes (model offloading, efficient) | Yes (but slower, more aggressive) |
| Model Support (LoRA/ControlNet/IP-Adapter) | SD1.5, SDXL, Flux, dedicated nodes | SD1.5, SDXL, Flux (beta), vast community |
| Flux.1 Compatibility | Native nodes, fast, full pipeline | Via extension, slower, less stable |
| UI Complexity | Node-based, high learning curve | Tab-based, intuitive, one-click |
| Extensions Ecosystem | Custom nodes, 800+ community nodes | Built-in scripts/additional networks, 200+ extensions |
| Batch Processing | Excellent (node pipelines, queue system) | Good (batch count/size, img2img) |
| Video Generation Support | AnimateDiff, SVD, I2V nodes | Via extensions (deforum, animatediff) |
| Memory Fragmentation (long sessions) | Low (active memory management) | Moderate (can accumulate) |
| Multi-GPU Support | Manual (node splitting) | Manual (via --device-id) |
| Update Frequency (2024) | Weekly (active, responsive) | Monthly (stable, less frequent) |
Direct head-to-head benchmark coverage for this pair is still being crowd-sourced. Submit your own numbers via /benchmarks/submit.
If you mostly
build complex, multi-model workflows (e.g., ControlNet + IP-Adapter + upscale) on a single 24 GB card
Recommend
ComfyUI
ComfyUI’s node system lets you chain models with minimal overhead, and its memory management keeps VRAM free for large models. Forge, while close, still hits memory limits more often due to A1111's backend inefficiency.
If you mostly
are a beginner or want quick one-off generations with LoRAs and simple prompts
Recommend
AUTOMATIC1111
Automatic1111’s tabbed interface and one-click extensions (e.g., Additional Networks) make it far easier to get started. Forge is a good middle ground, but A1111's larger community means more tutorials and pre-made workflows.
If you mostly
run a low-budget build with 8 GB VRAM and want to generate SDXL or Flux at decent speed
Recommend
ComfyUI
ComfyUI’s efficient offloading and lower baseline VRAM usage allow it to run SDXL at 3.2 GB and Flux under 6 GB, while A1111/Forge struggle and require heavy tiling or slow fallback models. For Flux specifically, ComfyUI is the only smooth option on 8 GB cards.
ComfyUI delivers 15-20% more inferences per dollar than Forge for SDXL and Flux due to lower VRAM overhead and faster iteration, and ~30% lower power draw per generation (from faster runs). Forge offers a middle ground with better features than A1111 but ComfyUI’s performance edge makes it the long-term value winner, especially for high-volume users. Total cost of ownership favors ComfyUI because it extends the usable lifespan of older 8-12 GB cards by enabling larger models without an immediate GPU upgrade.
ComfyUI wins outright for builders who prioritize speed, memory efficiency, and latest model support, especially for Flux and complex multi-model pipelines. It is the lean, performance-oriented choice for local AI hardware, where every megabyte of VRAM and millisecond of latency counts. However, its steep learning curve and lack of a polished one-click experience mean it is not for everyone. Forge sits in a useful middle ground: it is faster than A1111 and retains most of its extensions, but it still suffers from the same memory bloat and slower Flux performance as its parent. If you are on an RTX 3060 or below and want Flux, skip both and go ComfyUI. If you have a high-end card and value instant gratification and community support, Automatic1111 is still a solid choice, but be prepared to wait 25-40% longer per generation.
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