AI Image Generation: Local ComfyUI vs Midjourney/Jimeng — How Big Is the Gap? ​

Written in September 2026. AI technology moves fast, so the model capabilities, prices, and hardware requirements mentioned here reflect the situation at that time and are for reference only.

When people start paying attention to local AI, image generation is usually the first thing they want to try. After all, online services like Midjourney and Jimeng (即梦) are convenient, but they cost dozens to hundreds of yuan a month and still cap how much you can generate.

The question most people care about is: is the quality of locally generated images actually good enough?

Today we look specifically at image generation: what level local ComfyUI can actually reach, where the gap with Midjourney and Jimeng lies, and whether it's worth the effort.

Jimeng e-commerce image template

ComfyUI image workflow template

The conclusion first ​

If you're willing to spend time learning workflows, local image generation is already very close to commercial online services in quality. In certain specific styles and scenarios it can even do better.

But there are three preconditions:

1. You have a decent GPU (8GB of VRAM as a starting point; 16GB+ is more comfortable)
2. You're willing to spend a week or two learning the basics of ComfyUI
3. You can accept a working style where you build a workflow before you get an image

If all three hold, local image generation can fully meet everyday creative needs — cover images, illustrations, stock assets, memes, product shots: all of it is enough.

Which models can you run locally? ​

Most mainstream image generation models now have open source versions that can run locally:

Commercial licensing notes:

FLUX.2 Dev / klein 9B: released under the FLUX Non-Commercial License, so they cannot be used commercially as-is. Commercial use requires a license from Black Forest Labs. Personal learning and research are not restricted. If you need commercial use but want the FLUX family, choose FLUX.2 klein 4B (Apache 2.0).

Krea 2: released under the Krea-2 Community License. The following commercial scenarios are generally allowed: individual studio work, internal company tools, teaching at educational institutions, research projects. The following may require an additional license: SaaS platform integration, large-scale commercial deployment, redistribution or resale, enterprise-grade custom solutions.

Z-Image / Qwen-Image: Apache 2.0, free for commercial use.

All of these models can run in ComfyUI. ComfyUI is like an "AI drawing workbench": you freely combine models, plugins, and nodes to build a workflow that suits you.

Compared with online services, where's the gap? ​

1. Output quality: not much of a gap ​

In most scenarios, FLUX.2 Dev's output quality is already close to — or on par with — the latest version of Midjourney. Krea 2 has its own advantages in aesthetic style and texture. With a good workflow and LoRAs, an ordinary viewer probably can't tell the difference.

Where online services win:

• The default output has good taste — the "one sentence, one stunning image" experience is great
• The models are heavily optimized, so output is stable
• New styles and features ship fast

Where local wins:

• You can use targeted models and LoRAs to do better in specific domains (anime, photorealism, product shots)
• You can finely control every step — lighting, composition, character proportions, background elements
• Unlimited generation, with no need to worry about quotas

2. Barrier to entry: a big gap ​

This is local's biggest weakness.

With Midjourney or Jimeng, you type one sentence, wait a few dozen seconds, and get an image. Not happy? Click "vary" and get four more. Zero learning cost.

With ComfyUI? You need to understand what a "node" is, what a "workflow" is, what a "sampler" is, what a "LoRA" is... A first-time user may be completely lost.

To be fair, though:

• A basic text-to-image workflow is only seven or eight nodes — an afternoon of learning gets you going
• Plenty of ready-made workflows are available online to download and import
• Once you've built a workflow that suits you, all you do afterwards is tweak the prompt and generate — it's not slow

3. Cost: local wins outright ​

Not much to say here.

Online services: Midjourney Standard is $30/month (about ¥215), Jimeng's paid tier is about ¥69/month, and both cap your generations.

Local: a one-time GPU investment, then unlimited generation. If you do content creation or e-commerce and need dozens of images a day, local is enormously good value.

4. Freedom: local wins outright ​

This is the real reason many people choose local.

• Precise control with ControlNet: what pose the character strikes, where the hands go, how the background is structured — ControlNet gives you exact control. Online services can't get this fine-grained.
• Train your own style with LoRA: you can train a dedicated LoRA on your own product shots or your own art style, so every image comes out in your style.
• Batch generation and automation: once the workflow is built, you can generate in batches or automatically — ideal when you need large volumes of assets.
• Image editing: inpainting, background replacement, detail fixes can all be controlled precisely inside the workflow.

5. Privacy: local wins outright ​

Every image is generated on your own computer and never uploaded to any server. For commercial design, product shots, and internal assets, there's no worry about data leaks.

Hardware requirements ​

To run image generation locally, the GPU is the key.

Recommendation: if you want to get serious about local AI art, get at least 8GB of VRAM, preferably 12GB or more. Macs with M-series chips can also run ComfyUI, but some plugins and models aren't supported, so the experience is worse than with an NVIDIA card.

Who is it for, and who is it not for? ​

People suited to local ​

• High-volume creators: you need lots of images every day and online quotas aren't enough, or are too expensive
• People who need fine control: product shots, e-commerce images, design assets — you need exact control over the frame
• People who need a signature style: you want to train your own LoRA and keep a consistent look
• People who care about privacy: commercial projects and sensitive content you don't want on a third-party server
• People who enjoy tinkering: you're interested in AI technology and willing to spend time on it
• Design and art students: coursework and portfolios, with unlimited local generation and no quota worries
• Universities and training institutions: build an AI art lab with a unified teaching environment, where students get hands-on with how diffusion models work

People not suited to local ​

• People who want a minimal experience: you just want to type one sentence and get an image, and don't want to learn anything new
• People with low-spec computers: no discrete GPU, or less than 4GB of VRAM
• Occasional users: you only make a few images a month, so online services are better value
• People who don't want to touch technology at all: ComfyUI does have a learning curve

How to choose? A simple set of criteria ​

Ask yourself three questions:

1. How many images do you generate a month?

   • Fewer than 50 → online services are enough; don't bother
   • 50-200 → depends on whether you're willing to learn; if you are, local is better value
   • More than 200 → local will almost certainly save you money

2. How demanding are you about control over the frame?

   • Any decent image will do → online services
   • You need precise control over composition, characters, and style → local

3. Are you willing to spend time learning?

   • Not at all → online services
   • Willing to spend a week or two getting started → local

Where do you start? ​

If you want to try local AI art, here's how to get started:

1. Check your computer's specs first — GPU model, VRAM, system RAM
2. Download 魔当 — install ComfyUI in one click, without setting up Python, CUDA, and the rest yourself
3. Find a basic text-to-image workflow — there are plenty online; import and go
4. Start with FLUX.2 or Krea 2 — currently the most mainstream open source models with the most reliable results. If VRAM is limited, try FLUX.2 klein first
5. Learn ControlNet and LoRA gradually — these two are local art's real killer moves

We'll write more about practical ComfyUI techniques later on.

If you need images every day, or you're spending a fair amount on online services, local deployment is genuinely worth trying. Spend a week learning up front, and the time and money you save afterwards are all profit.