Redraw vs Stable Diffusion and ComfyUI: Specialist AI vs Open Source AI for Architecture
Stable Diffusion and ComfyUI for architecture rendering: $3,000 GPU, 80 GB of models, and infinite curve. Or Redraw in 30 seconds in the browser.

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You watched a YouTube video showing incredible renders made with Stable Diffusion and ComfyUI. The guy built a workflow, installed some LoRAs, connected some nodes, and generated a photorealistic interior image. It looks magical. And it's free.
Then you try to replicate it.
You install ComfyUI. Download the base model (6 GB). Discover you need architecture-specific LoRAs (another 3 to 10 GB each). Connect the nodes wrong. The result comes out distorted. Search for a tutorial. Another tutorial. Update the model. The GPU can't handle it. The render crashes. Try another model. That's 80 GB of downloads. The card overheats. Results improve, but nowhere close to the video. Two days have already passed.
That's the real path of Stable Diffusion for anyone who isn't a developer. And that's what no influencer talks about.
What Stable Diffusion and ComfyUI actually require
Let's be direct about the requirements to use SD/ComfyUI for architectural rendering at professional quality.
Hardware: Good AI models (SDXL, architecture fine-tuned models, high-quality LoRAs) weigh 80 GB or more in total. To run them at acceptable speed, you need a GPU with at least 12 GB of VRAM. In practice, that means an RTX 4080 or 4090. The 5080 and 5090 are already on the market and are the new standard for anyone taking this seriously. We're talking about cards that cost between $1,500 and $4,000. Just the card. Add the rest of the PC and easily pass $5,000.
Technical knowledge: ComfyUI is a node-based interface. Each workflow is a chain of connections between models, samplers, schedulers, controlnets, upscalers. To build a workflow that works for architecture, you need to understand what each node does. You need to know the difference between checkpoint and LoRA, between Euler and DPM++, between txt2img and img2img with ControlNet. That's not an architect's knowledge. That's a developer's knowledge.
Constant updates: The open-source AI ecosystem changes every week. New models, new nodes, new techniques. The workflow that worked last month might be obsolete. Even people who study AI daily can't test and validate everything. For an architect with projects to deliver, keeping that pace is impossible.
Result: Yes, you can reach impressive results. But the cost in time and money to get there is disproportionate. And consistency is low. Each render comes out different. Every model or parameter change alters everything.
What nobody tells you about SD for architecture
Stable Diffusion is fully customizable. That's true. If you have development knowledge, time to train models, and hardware to run them, you can create tailored results. For architectural visualization studios with dedicated technical teams, it can make sense.
But for the professional who wants to use AI to increase productivity and quality day-to-day, it's inaccessible. Not in the sense of "difficult." In the sense that the investment in time and money doesn't pay off.
A solo architect who spends 2 weeks learning ComfyUI, $3,000 in hardware, and still has to keep updating workflows every week, could have solved the same problem with $15/month on Redraw. In 30 seconds. In the browser.
What Redraw does differently
Redraw has a team of AI specialists thinking daily about how to improve the models. Testing new releases, refining, validating what works for architecture and discarding what doesn't. It's the work you'd have to do alone with SD/ComfyUI, but done by people who understand it.
The result: rendering models that reach a level of hyper-realism that generic SD doesn't reach without heavy fine-tuning. And that result is available to anyone, with no installation, no configuration, no dedicated GPU.
Inside Redraw, you access ChatGPT optimized for render, Nano Banana, Gemini, and Redraw's own models. All trained and tuned for architecture, engineering, and interior design. It's the best of what the open-source ecosystem offers, curated and optimized, without you needing to become an AI engineer.
Comparison: Stable Diffusion/ComfyUI vs Redraw
Who SD/ComfyUI makes sense for
If you're a developer, AI enthusiast, or work at a visualization studio with a dedicated technical team, Stable Diffusion is a legitimate option. Total customization lets you create tailored pipelines and train models specific to your niche.
It also makes sense if you want to understand how AI works under the hood. ComfyUI is an excellent educational tool. You learn concepts of diffusion, sampling, ControlNet, LoRA. Valuable knowledge.
Who Redraw is better for
For everyone who is an architect, engineer, or interior designer and wants results, not to become an AI specialist.
If your job is to design and deliver, not configure 47-node workflows, Redraw solves it. In 30 seconds. Without $3,000 in hardware. Without 2 weeks of learning. Without going obsolete next month.
Professionals who try to enter the SD world without technical background are swallowed by complexity. Not because they're incapable. Because it's not their job. Just as an AI developer shouldn't need to learn architecture to render a house, an architect shouldn't need to learn how to configure samplers to get a professional render.
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