Somewhere in your first week of AI image generation, you will hear two voices.

The first says: “Just use Midjourney. It works. You type, you get images.”

The second says: “Run it locally. It is free. You have full control. Install ComfyUI, download the Flux weights, configure your VRAM allocation…”

Both are right. Both are incomplete. Here is the honest version.

The two paths

Cloud means you use a website or app. Your prompts go to someone else’s computers. They generate the image. You pay per image, per month, or per credit. You need nothing but a browser.

Local means you run the AI model on your own computer. You download the model files (several gigabytes), install software to run them, and generate images using your own hardware. Once set up, there is no per-image cost.

Most creative professionals start with cloud and stay there. Some move to local for specific reasons. A few run both. Here is how to decide.

Cloud: the honest picture

What you get:

  • Working in minutes. Sign up, type, generate.
  • No hardware requirements beyond a browser (or phone)
  • Automatic updates — new models appear without you installing anything
  • Multiple models in one place if you use a platform like Flora Fauna (80+ models on one canvas)
  • Consistent results regardless of your computer’s age

What it costs:

  • Midjourney: $10-60/month depending on tier
  • Flora Fauna: from $18/month with 20,000 credits
  • Google’s Nano Banana: free tier (10 images/month), then $19.99-249.99/month
  • Individual API calls: $0.01-0.10 per image depending on model and resolution

Who it is for:

  • Everyone starting out. No exceptions.
  • Professional creatives who need reliability and speed
  • Anyone working from a laptop, tablet, or phone
  • People who use multiple models for different jobs (photo-realism from one, illustration from another)

The honest downside:

  • You are renting. If the service goes down or changes pricing, your workflow breaks.
  • Some models are only available locally (custom fine-tunes, niche models)
  • At very high volume (thousands of images per month), the per-image cost adds up

Local: the honest picture

What you get:

  • No per-image cost once set up
  • Total privacy — nothing leaves your machine
  • Access to the full ecosystem of open-source models (Stable Diffusion, Flux, custom fine-tunes, LoRAs)
  • Complete control over every parameter
  • No content policy restrictions (for better and worse)

What it costs:

  • A GPU with at least 8GB of VRAM. Realistically, 12-24GB for comfortable work. This means an NVIDIA RTX 3060 at minimum ($250-400 used) or an RTX 4090 for serious work ($1,500+)
  • Time. A lot of time. Setting up ComfyUI, downloading model weights, installing dependencies, troubleshooting driver conflicts.
  • Ongoing maintenance. Models update. Software breaks. New versions require new dependencies.

Who it is for:

  • People who generate thousands of images per month and want to eliminate marginal cost
  • Technical users who enjoy (or at least tolerate) system configuration
  • Artists who need custom-trained models (LoRAs, fine-tunes) that are not available on cloud platforms
  • Privacy-sensitive work that cannot leave your machine

The honest downside:

  • The setup cliff is real. “It took me eight hours to generate my first image with Flux” is a direct quote from r/StableDiffusion. This is not unusual.
  • Your results depend on your hardware. A laptop GPU produces different quality than a desktop GPU.
  • When something breaks (and it will), you are your own tech support.
  • You are limited to one model at a time unless you have a very powerful machine.

The decision framework

Answer these four questions:

1. How many images do you generate per month?

  • Under 500: Cloud is almost certainly cheaper, even at paid tiers
  • 500-2,000: Depends on the model and your hardware. Could go either way.
  • Over 2,000: Local starts to make financial sense — if you have the hardware

2. Do you need custom models?

  • If you are fine with the major models (Nano Banana, Flux, Midjourney), cloud has everything you need
  • If you need custom LoRAs, specific fine-tunes, or models not available on cloud platforms, you need local (at least partially)

3. How much time do you want to spend on setup and maintenance?

  • If your answer is “zero,” cloud is the only option. Local requires ongoing attention.
  • If you enjoy tinkering (some people genuinely do), local can be deeply satisfying.

4. What hardware do you have?

  • Laptop with integrated graphics: Cloud only. No discussion.
  • Desktop with an NVIDIA GPU (8GB+ VRAM): Local is possible.
  • Mac with M-series chip: Local works for some models (Stable Diffusion, Flux), but slower than an equivalent NVIDIA GPU. Getting better every month.
  • Desktop with 24GB+ VRAM: Full local capability.

The answer for most people

Start with cloud. Move to local later if you have a specific reason.

This is not a cop-out. It is practical advice. Cloud gets you generating images today. Local gets you generating images after hours of setup, troubleshooting, and hardware investment. The creative skill — describing what you want, iterating on results, building a consistent style — is the same on both platforms. Learn the skill first on the easiest surface.

If you eventually outgrow cloud — because of volume, cost, or the need for custom models — you will be a much better judge of what local setup you need. “I need Flux with a specific LoRA for product photography at 4K” is a very different setup from “I want to try local AI.” Specificity makes the setup easier because you know what to ignore.

The hybrid approach

Many professional AI creatives end up running both:

  • Cloud for daily work. Fast, reliable, multiple models. This is where the bulk of images get made.
  • Local for special cases. Custom models, private work, high-volume batch runs, experimental workflows.

This is the setup the AI Creative’s Toolbox describes in more detail — the full stack of what is available and how the pieces fit together.

One more thing

If you are reading this and feeling overwhelmed by the choice, that is the tool selection paralysis talking. It is the number one reason people delay starting. The answer is simple: pick any cloud platform and generate your first image today. You can always change platforms later. The prompting skill transfers everywhere.

Art & Algorithms publishes guides, tutorials, and prompt packs at the intersection of art and code. Subscribe for the full archive.