MLA 025 AI Image Generation: Midjourney vs Stable Diffusion, GPT-4o, Imagen & Firefly

Multimedia Generative AI Mini Series

• Part 1: Image Generation
• Part 2: Video Generation
• Part 3: End-to-End Workflow

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The 2025 generative AI image market is defined by a split between two types of tools. "Artists" like Midjourney excel at creating beautiful, high-quality images but lack precise control. "Collaborators" like OpenAI's GPT-4o and Google's Imagen 4 are integrated into language models, excelling at following complex instructions and accurately rendering text. Standing apart are the open-source "Sovereign Toolkit" Stable Diffusion, which offers users total control, and Adobe Firefly, a "Professional's Walled Garden" focused on commercial safety.

The Five Main Platforms

The market is dominated by five platforms with distinct strengths and weaknesses.

Platform Analysis

• Midjourney v7: Delivers the best aesthetic and photorealistic quality via a new web UI. Its "Draft Mode" allows for rapid, low-cost ideation. However, it cannot reliably render text, struggles to follow precise instructions (like counting objects), makes all images public on cheaper plans, and strictly prohibits API access or automation.
• GPT-4o: Its strength is conversational refinement within ChatGPT, allowing users to edit images through dialogue (e.g., "change the shirt to red"). It has excellent instruction-following and text-rendering capabilities. Weaknesses include being slower than competitors and generating only one image at a time.
• Google Imagen 4: A practical tool integrated directly into Google Workspace and Gemini. It produces high-quality, high-resolution (2K) photorealistic images quickly and renders text well. Its primary advantage is letting users generate images without leaving their documents or presentations.
• Stable Diffusion 3 (SD3): An open-source model that provides users with total control and privacy. The new SD3 architecture significantly improves prompt understanding and text generation. It can run on consumer hardware, and its quality is free after the initial hardware cost. Its power comes from a vast ecosystem of community tools (see below), but it has a steep learning curve.
• Adobe Firefly: Embedded within Adobe Creative Cloud (e.g., Photoshop's Generative Fill). Its key differentiator is commercial safety; it is trained only on licensed Adobe Stock and public domain content to indemnify users from copyright claims. It excels at editing existing images rather than generating from scratch.

Techniques & Tools

• In-painting/Out-painting: Core editing functions. In-painting modifies a specific area within an image. Out-painting expands an image beyond its original borders.
• Stable Diffusion Power Tools:
  • LoRAs (Low-Rank Adaptations): Small files that apply a specific style, character, or concept to the main model.
  • ControlNet: A framework that uses a reference image (e.g., a sketch or a stick-figure pose) as a "blueprint" to enforce a specific composition or pose.
• Stable Diffusion Interfaces: Users choose a UI to run the model. Automatic1111 is a beginner-friendly, tab-based dashboard. ComfyUI is a more complex but powerful node-based interface for building custom, automated workflows.

Feature Comparison & Exclusion Rules

The choice of tool often depends on a single required feature.

This leads to several hard rules for choosing a tool:

• If you need accurate in-image text: Exclude Midjourney. Use GPT-4o, Google Imagen 4, or specialist tool Ideogram.
• If you require absolute privacy or must run locally: Stable Diffusion is your only option.
• If you require a guarantee of commercial safety: Adobe Firefly is the most prudent choice.
• If you need to automate generation via an API: Use OpenAI or Google's official APIs. Midjourney bans automation and will close your account.

Global Ranking

Finally, I like to force Gemini Deep Research to rank tools globally based on score, with a final rank based on the sum. It hates doing this, but I have my ways. Take this with a grain of salt - choose based on how the tool fits your needs - but this can be a handy starting point:

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Part 1: The AI Image Market is Split into Different Tool Types

Two Types of AI Image Tools: "Artists" and "Collaborators"

AI image generators have split into two main groups. Each is good at different things. Understanding the split helps you pick the right tool for a job.

The first group is the "Artist" tools. These are built for artistic quality, creating beautiful, cinematic, and opinionated images. Their goal is visual flair. Midjourney is the best example of this. It produces images with a professional, polished feel that can be breathtaking. However, this focus on art means you get less control. These tools often misunderstand complex instructions, can't create readable text, and don't place objects precisely. They act more like a temperamental artist than a reliable tool.

The second group is the "Collaborator" tools. These tools, like OpenAI's GPT-4o and Google's Imagen 4, are part of larger language models (LLMs). Their main strength is not just creating an image, but working with you through conversation. They are very good at understanding detailed instructions, creating accurate text, and fitting into other work software. They act like smart partners that refine an image based on your feedback, making them useful for business and design work where you need precision.

This split comes from the different goals of their parent companies. OpenAI and Google are data and logic companies, so their image tools are built to follow instructions and understand context. Midjourney calls itself an "independent research lab exploring new mediums of thought" and focuses only on expanding "the imaginative powers of the human species." This is why GPT-4o can "think" through a complex logo design, while Midjourney "feels" its way to a beautiful fantasy image that might ignore your prompt.

A third type of tool is the "Sovereign Toolkit," like Stability AI's Stable Diffusion. It is an open-source model that gives users full control, customization, and privacy. It's a powerful engine for a large community of users, but it requires more technical skill to use.

The Key Players in 2025

This report focuses on the main platforms that dominate the market. These are the tools you need to know to be competitive.

The five main platforms are:

• Midjourney (v7): The leader in artistic and aesthetic quality.
• OpenAI (GPT-4o): The best conversational tool, built into ChatGPT.
• Google (Imagen 4): A practical and fast tool, built into the Google ecosystem.
• Stability AI (Stable Diffusion 3): The open-source standard for total control and customization.
• Adobe (Firefly): The professional choice for commercially safe images integrated into Adobe products.

Other tools are important for specific jobs. Ideogram is known for having the best text generation, often doing better than the bigger models on this one difficult task. FLUX.1, from a team with roots in Stable Diffusion, is a new open-source option that creates high-quality images and follows prompts well.

2025 AI Image Tool Comparison

Part 2: The Top 5 AI Image Platforms in Detail

Midjourney v7: Best for Artistic Quality, but Lacks Control

What it is In 2025, Midjourney is the top choice for users who want final image quality, artistic style, and cinematic realism above all else. It acts like an artist, producing images that are often called the most "beautiful" and "artistic" available. Its images often look like professional concept art, making it the favorite tool for illustrators and designers who need inspirational, high-quality pictures.

Key Features (v7) Version 7, released in early 2025, added several important updates.

• Web Interface & Draft Mode: Midjourney now has a full web application, moving beyond its original Discord-only interface. A new feature is Draft Mode, which lets you generate lower-quality images quickly and for half the cost. It is designed for fast brainstorming before you commit to creating a high-quality "enhanced" version. This solves a major problem from older versions, which used a lot of time and credits for every small change.
• Personalization: V7 requires you to set up a personalization profile by rating about 200 image pairs. This trains the model on your personal taste, allowing Midjourney to adjust its output to better match what you like over time.
• Better Prompts & Quality: V7 is better than v6 at following instructions, though it still lags behind its competitors. It handles longer prompts more accurately and creates images with more realistic textures, especially skin, as well as better-formed bodies and hands.
• Video & 3D Are Coming: Midjourney is developing text-to-video and 3D model features. The video feature in v7 can create short clips (like 60 seconds from six images) and is known for its high artistic quality. The 3D features aim to create "NeRF-like" models, which would let you change camera angles and explore scenes in 3D.

Weaknesses & Risks

• Poor Control & Text Generation: This is Midjourney's biggest weakness. It struggles with precise instructions. It often ignores negative prompts, can't count objects correctly, and can't reliably place items in specific locations. Its inability to create readable text is a major flaw, often called "embarrassing" by users who need text for logos or posters. This has earned it the reputation of an "artistic genius with a learning disability".
• Privacy and Commercial Use Risks: On cheaper plans (Basic at $10/month, Standard at $30/month), all images you create are public by default. To make your images private ("Stealth Mode"), you must subscribe to the Pro ($60/month) or Mega ($120/month) plans. This makes cheaper plans unsafe for any confidential work.
• No API and Hostile to Automation: Midjourney does not offer an API for developers. Its rules also forbid automation, and the company is known to ban users who try to build tools to automate workflows. This "walled garden" approach shuts out developers who want to use Midjourney inside their own apps.

Midjourney's closed system is why it has such a unique artistic style. But this same approach makes it slow to add useful features like text generation and hostile to developers. This forces many professionals to start in Midjourney to get a beautiful image, but then move to other tools to finish the work with more precision.

GPT-4o: Best for Control Through Conversation

What it is OpenAI's GPT-4o is a conversational partner that can create images. Its main feature is not the image itself, but the intelligent way it follows your instructions. By building image generation directly into ChatGPT, OpenAI created a tool whose main advantage is its deep understanding of language, giving you a level of control through dialogue that was not possible before. It works with you to create an image, rather than just taking an order.

Key Features

• Conversational Refinement: This is the tool's killer feature. You can change an image through a conversation. After generating an image, you can give simple commands like, "make the background a solid black," "add a company logo to the top left corner," or "change the character's shirt to red". GPT-4o remembers the context and applies the changes, acting like a human designer taking direction from a creative director.
• Excellent Instruction Following & Text: Because it's based on a powerful language model, GPT-4o is great at understanding and executing complex prompts. It can handle instructions with many objects (10-20) and their relationships. It has also largely solved one of the hardest problems in AI imaging: creating clear, readable, and correctly spelled text. This makes it a great tool for practical uses like logos, posters, and diagrams where text is required.
• Learns from Uploaded Images: GPT-4o can analyze images you upload. This allows for powerful image-to-image work. You can upload a photo and ask the model to change it, copy its style, or use it as a reference for a new image. For example, you could upload a sketch and ask for it to be turned into a polished user interface mockup.
• Versatile for Practical Uses: This combination of precision and conversational control makes GPT-4o very effective for creating "useful" images. It is a top choice for making UI/UX prototypes, technical diagrams, and marketing materials where following requirements is more important than artistic style.

Weaknesses

• Slow Speed and Low Output: GPT-4o is much slower than competitors like Google's Imagen 4. It also only generates one image at a time, which can be a problem for brainstorming when you need to see many options at once.
• Less Artistic Style: While versatile, its images are often seen as less artistic than Midjourney's. Some users find them "mediocre" and note a tendency towards a generic, slightly "yellow" or "sepia" color tone that can be hard to remove.
• Strict Content Rules: Users report that OpenAI's content safety rules have become very strict and are sometimes unclear. The model may refuse to generate images for seemingly harmless prompts or will refuse to reference copyrighted styles, which can be frustrating.

The true innovation of GPT-4o is the process, not just the final image. By embedding image generation inside a conversational AI, OpenAI has changed the user's role from a "prompter" to a "creative director." This makes it the go-to tool for "stuff that actually needs to WORK".

Google Imagen 4: Best for Integration into Google Apps

What it is Google's Imagen 4 is a fast, practical, and high-quality image generator. Its main advantage is its deep integration into the Google ecosystem of apps. It is designed to bring image generation into the daily work of millions of business, education, and enterprise users.

Key Features

• Photorealism and Detail: Imagen 4 can produce high-quality, realistic images up to 2K resolution. It is good at rendering fine details like fabric, water droplets, and animal fur.
• Speed and Text Rendering: A key feature is its speed. Imagen 4 has a "fast mode" that is reportedly up to 10 times faster than its predecessor, Imagen 3. Like GPT-4o, it is very good at creating accurate text, which is important for making branded images, presentations, and educational content.
• Google App Integration: This is Imagen 4's biggest advantage. Google is putting the model directly into its main apps, including Google Workspace (Docs, Slides, Vids), the Gemini chatbot, and its developer platform, Vertex AI. This lets you generate custom images with simple text prompts without ever leaving your document or presentation.
• Multilingual Support: The model supports prompts in many languages, making it useful for global teams.

Weaknesses

• Limited Artistic Style: While technically good, Imagen 4 is not known for having a unique artistic style like Midjourney. It is more focused on producing accurate and high-quality results than inspiring art.
• Dependent on Google Apps: Its greatest strength is also a potential weakness. You get the full value of Imagen 4 only if you use Google's other products. For people who don't use Google Workspace or Vertex AI, its benefits are less appealing.

Google's strategy with Imagen 4 is clear. Instead of trying to "out-art" Midjourney, Google is using its biggest asset: its popular productivity apps. By putting Imagen 4 directly into the apps where millions of people already work, Google is making AI image generation a simple, everyday tool. The ability to create the perfect image for a slide deck without switching apps is a powerful advantage that no standalone tool can offer. This strategy aims to capture the huge market of business professionals, marketers, and educators, making convenience its main selling point.

Stable Diffusion 3: Open-Source Tool for Maximum Control and Customization

What it is Stable Diffusion is the leading open-source image generator. It is not a single product but a core model that powers a huge community. Its main purpose is to give users total control, endless customization, and complete freedom, if they are willing to learn the technical details. With Stable Diffusion, you are the master of your own image generator.

Key Features (SD3)

• New MMDiT Architecture: Stable Diffusion 3 has a new architecture that is a big step forward. It uses separate sets of programming for processing text and images. This helps the model better understand complex prompts and create more accurate text and spelling, fixing the biggest weaknesses of older versions.
• Scalable and Efficient: Stability AI has released SD3 in various sizes, from a small 800 million parameter model to a large 8 billion parameter model. This means it can run on standard consumer computers (like an NVIDIA RTX 4090) while still offering top performance for those with more powerful hardware. It also uses a technique called Rectified Flow, which makes generation faster, allowing for high-quality images in fewer steps.
• The Unbeatable Control Ecosystem: The true power of Stable Diffusion comes from the huge number of community-built tools that expand what it can do.
  • User Interfaces: You can choose between interfaces like Automatic1111 (more beginner-friendly) and ComfyUI, a node-based system that offers total flexibility for building complex, automated workflows.
  • Detailed Customization: Tools like LoRAs and ControlNet provide a level of fine-grained control that is not available in other models. LoRAs let you train the model on specific characters or styles, while ControlNet gives you precise control over composition and pose using reference images. These are explained more in Part 3.
  • Privacy, Freedom, and Cost: Since Stable Diffusion can run on your own computer, it offers complete privacy. There are no content filters, and no company is watching what you create. Once you have the computer hardware, creating images is completely free, making it the cheapest option for high-volume work.

Weaknesses

• Steep Learning Curve: Using Stable Diffusion's full power is not easy. You have to learn how to use different interfaces, install models and extensions, and understand technical concepts. This can be a major hurdle for non-technical users.
• Quality Depends on the User: Unlike the curated images from a tool like Midjourney, the quality of Stable Diffusion images depends heavily on your skill. Your choice of model, LoRAs, prompts, and settings all have a big impact on the final result.

It's wrong to compare Stable Diffusion directly to a product like Midjourney. Midjourney and GPT-4o are products that offer a specific experience. Stable Diffusion is an open-source platform, an engine for building custom experiences. Its value is in its endless ability to be extended and the control it gives the user. The community on sites like Civitai and Hugging Face constantly creates new models and tools, making it a dynamic and ever-growing toolkit. This makes Stable Diffusion the best choice for the power user, developer, researcher, and anyone who wants to build a custom image factory instead of just renting one.

Adobe Firefly: Best for Commercial Safety and Photoshop Integration

What it is Adobe Firefly is Adobe's AI tool, deeply built into its Creative Cloud software. It is not meant to be a standalone tool, but a powerful feature set within Adobe's existing products. Its purpose is twofold: to provide AI features inside professional workflows and, most importantly, to be the leader in commercial safety.

Key Features

• Deep Creative Cloud Integration: Firefly is delivered through Adobe's main applications. Features like Generative Fill, Generative Expand, and Generative Recolor are now part of Photoshop and Illustrator. This means designers and photographers can use AI without ever leaving the software they already know.
• Commercially Safe by Design: This is Firefly's biggest selling point for businesses. The Firefly model was trained only on Adobe's own library of licensed Adobe Stock images and public domain content with expired copyrights. This "clean" training data is designed to protect users from the copyright and ethical problems that affect models trained on data scraped from the internet. Adobe guarantees that images made with Firefly are safe for commercial use, providing a level of legal security that other platforms can't offer.
• Workflow-Focused Tools: Firefly's features are built for editing and improving images, not just creating them from scratch. Generative Fill, for example, lets you select an area of a photo and replace it with new content based on a prompt. Generative Expand smartly extends the borders of an image. These tools help creative professionals with their daily tasks.

Weaknesses

• Creative Limits: The very thing that makes Firefly safe, its training data, may also limit its creativity. Since it wasn't trained on the vast and diverse images of the internet, it may not be as good at recreating specific, niche art styles compared to Midjourney or Stable Diffusion.
• Subscription Required: Full access to Firefly is tied to an Adobe Creative Cloud subscription, making it a more expensive option than free or cheaper tools. Usage is also limited by a system of "generative credits".

Adobe's strategy with Firefly is smart. First, it's a defense. By building powerful AI features directly into Photoshop, Adobe gives its users little reason to leave for other tools, protecting its main business. Second, it's a bridge. By positioning AI as an editing tool (like Generative Fill) and guaranteeing commercial safety, Adobe makes AI adoption easier and less threatening for its audience of creative professionals and agencies.

Part 3: Key Techniques for Advanced AI Image Editing

In-painting and Out-painting: How to Edit and Expand Images

In-painting and out-painting are two of the most basic and powerful editing techniques. They turn the AI from a simple generator into an editing partner.

• In-painting: The Magical Spot-Fixer
  • Concept: In-painting is the process of changing, replacing, or fixing a specific area inside an image. You define a "mask" (the area to be changed), and the AI re-creates the content inside that mask based on the surrounding pixels and an optional new text prompt.
  • Analogy: Think of it as a smart spot remover. Imagine a perfect photo of a room with an unwanted chair in the corner. With in-painting, you just draw a mask over the chair. You can then leave the prompt blank, and the AI will fill in the space as if the chair was never there. Or, you could give a prompt like "a tall green plant," and the AI will replace the chair with a new object that perfectly matches the scene's lighting and style. This is great for fixing errors (like bad hands), removing objects, or adding new things to a scene.
• Out-painting: Expanding the Canvas
  • Concept: Out-painting (or "Generative Expand" in Photoshop) is the process of extending an image beyond its original borders. The AI analyzes the edges of the image and generates new content to expand the picture.
  • Analogy: Imagine you have a beautiful portrait, but it's a tight close-up, and you want to see more of the background. Out-painting is like asking an artist, "Show me what's just outside the frame." The AI looks at the existing image and paints what would logically continue beyond the original edges, effectively "zooming out" of the original shot to create a wider scene.

These two techniques are fundamental to almost every serious AI editing workflow. They are found in Stable Diffusion UIs in the img2img tab and are the core functions of Adobe's "Generative Fill" and "Generative Expand" tools.

Stable Diffusion's Power Tools: LoRAs and ControlNet

Stable Diffusion's open-source community has created powerful tools that offer a level of control that other platforms can't match. The two most important are LoRAs and ControlNet. Together, they turn Stable Diffusion from a random generator into a precision tool.

LoRAs: Teaching the AI a Specific Style or Character

• Concept: A LoRA (Low-Rank Adaptation) is a small file (10-500 MB) that applies a specific, fine-tuned change to a standard Stable Diffusion model. They are an efficient way to teach the AI a new, specific concept, like a person's face, a unique art style, or a particular object, without retraining the entire large model.
• Analogy: Imagine your main Stable Diffusion model is a master chef who knows how to cook everything. This is your main model. Now, imagine you want the chef to make your grandmother's secret lasagna. You wouldn't make the chef go back to culinary school. Instead, you would hand them a single recipe card for that one dish. The recipe card is the LoRA. The chef uses all their existing knowledge but applies the specific instructions from the card to make the perfect lasagna.
• Common Types of LoRAs: There is a huge library of community-created LoRAs on sites like Civitai:
  • Character LoRAs: Trained on a specific person or character to create consistent images of them.
  • Style LoRAs: Trained on a specific artist or aesthetic (e.g., "Ghibli style") to apply that look to any image.
  • Concept LoRAs: Trained on an idea or object (e.g., "glass sculptures") that is hard to describe with words.
  • Clothing and Pose LoRAs: Specialized models for applying specific outfits or forcing certain poses.

ControlNet: Controlling Composition and Pose with a Reference Image

• Concept: ControlNet is a framework that works with Stable Diffusion to add another layer of control. While a text prompt tells the model what to create, ControlNet uses a reference image to tell it how and where to create it, enforcing a specific structure or pose.
• Analogy: If a text prompt is like telling an architect you want "a modern two-story house," ControlNet is like handing them a detailed blueprint. The blueprint defines the house's structure, like the position of the walls and the shape of the roof. The architect (Stable Diffusion) is still free to be creative with the materials and decor (the style and details), but they must follow the blueprint (the ControlNet map). It's like a paint-by-numbers kit where the lines are already drawn for you.
• Key ControlNet Models: ControlNet first analyzes a source image to extract a structural "map." The most popular types include:
  • OpenPose: Detects the human body in an image and extracts a "stick figure" skeleton of their pose. This is the best way to copy a human pose perfectly.
  • Canny / Lineart: These detect the hard edges or outlines in an image. This is perfect for copying a composition or turning a sketch into a full image.
  • Depth: This creates a map of the 3D layout of a scene. This allows you to copy the perspective of a scene even if you change all the objects and the style.
  • Normal Map: Creates a map of surface geometry, which is great for keeping fine surface details while changing the style.

LoRAs and ControlNet turn image generation from a game of chance into an act of intention. LoRAs provide consistency for characters and styles, while ControlNet provides consistency for structure and poses. The combination of these two tools is what allows you to create complex visual stories and precise commercial images.

Choosing a Stable Diffusion Interface: Automatic1111 vs. ComfyUI

If you choose to use Stable Diffusion, you must select a user interface (UI). The two main choices, Automatic1111 and ComfyUI, represent a trade-off between ease of use and ultimate power.

• Automatic1111 (A1111): The User-Friendly Dashboard
  • Description: A1111 is a popular interface for Stable Diffusion that uses a traditional, tab-based layout that is easy for most users to understand. It has tabs for key functions, making it fairly easy for a beginner to get started.
  • Strengths: A1111 is more beginner-friendly. Its interface makes common tasks, especially editing one image repeatedly, very simple. It also has a huge community and many extensions for adding new features.
  • Weaknesses: It is less memory-efficient than ComfyUI. More importantly, its workflow is "destructive." Once you perform a step, you can't go back and change an earlier setting without starting over. This makes complex, multi-step projects inefficient.
• ComfyUI: The Modular "Flowchart" Factory
  • Description: ComfyUI uses a node-based interface where you build your image pipeline visually by connecting blocks together, like a flowchart. Each block represents a step in the process (e.g., "Load Model," "Encode Prompt," "Generate Image").
  • Strengths: ComfyUI offers endless flexibility and better performance. It is more memory-efficient, allowing for higher-resolution images on the same hardware. Its real power is its "non-destructive" nature. You can build complex workflows that run multiple processes at once. You can change any setting at any point, and only the affected parts of the workflow will re-run. This makes it the best choice for automation, complex experiments, and video generation.
  • Weaknesses: ComfyUI has a much steeper learning curve. It requires you to understand how Stable Diffusion actually works. Simple tasks can require connecting multiple nodes, which can be frustrating for beginners.

The choice is clear. A1111 is for the user who wants to drive a powerful car with a familiar dashboard. ComfyUI is for the user who wants to build their own custom engine from scratch.

Stable Diffusion UI Comparison

Part 4: How to Combine Tools for Professional Results

Workflow 1: Midjourney for Art, Photoshop for Control

This is the most popular professional workflow. It combines the strengths of the best platforms. The workflow uses Midjourney's powerful engine to create a beautiful base image, then uses Adobe Photoshop's precision tools (powered by Firefly AI) for the essential tasks of editing, cleanup, and adding elements that need perfect control. This pipeline exists because no single tool is good at everything.

Step-by-Step Guide:

1. Create a Base Image in Midjourney: Start in Midjourney, focusing only on artistic quality. Craft prompts that prioritize mood, lighting, and composition. Use parameters like style references (--sref) to guide Midjourney's style. Your goal is to get a visually stunning base image. Once you have one, use Midjourney's upscaler to get the highest resolution version.
2. Clean Up in Photoshop: Import the upscaled image into Photoshop. The first step is often cleanup, as Midjourney images can have small errors or artifacts. For large fixes, use Photoshop's AI-powered Generative Fill. Select an unwanted object and run Generative Fill with a blank prompt to intelligently remove it.
3. Composite and Expand in Photoshop: This is where Photoshop and Firefly's control really matter. To expand the image, use the Crop Tool to extend the canvas and then use Generative Expand to fill the new space with content that matches the original image. To add new objects, use Photoshop's selection tools to define the area, then use Generative Fill with a detailed prompt. Firefly's engine will try to match the lighting and perspective of the original Midjourney image. You can also use this step to combine parts of different Midjourney images into one scene.
4. Finish and Brand in Photoshop: Use Photoshop's professional tools to complete the image. Add text or logos with the Type Tool. Perform final color grading and sharpening using Adjustment Layers.

Workflow 2: Staying in One System (Adobe or Google)

For many teams, the best workflow is one that stays inside a single software system.

• The Adobe Creative Cloud Workflow: This workflow is for creative professionals who already use Adobe's software. The main benefit is the smooth flow between creating and editing, all within a commercially safe system. A designer might generate concepts in the Firefly web app, bring an image into Photoshop to use Generative Fill to add a product mockup, and then use Generative Recolor in Illustrator to explore new color palettes with a simple prompt like "autumn tones." The guarantee of commercial safety makes this the top choice for agencies and large companies.
• The Google Workspace Workflow: This workflow is for business users and educators. The goal is to make image creation an easy part of everyday work. A manager building a presentation in Google Slides can now use the integrated Imagen 4 panel to type a prompt directly into Slides. The AI generates the image and inserts it with one click. The value is in speed and convenience, eliminating the need to switch apps, which breaks focus and slows down work.

Workflow 3: Building Automated Pipelines with ComfyUI

For the ultimate power user, the goal is to build an automated image generation factory. This is what ComfyUI is for, as its node-based system lets you create complex, repeatable workflows that are impossible in other interfaces. This is ideal for tasks that need consistency, batch processing, or a sequence of complex steps.

Examples of advanced ComfyUI workflows:

• Automated Upscaling and Detailing: You can build a workflow that generates a base image, sends it to an upscaler, then sends that output to both a face-fixing tool and a hand-fixing tool, and then combines the results. This entire multi-step process runs with a single click.
• Consistent Characters in Multiple Poses: You can load a Character LoRA to define a character's appearance, then feed that into multiple ControlNet nodes, each with a different pose. When you run the workflow, it will generate images of the exact same character in all the specified poses at once.
• Complex Style Blending: The node system allows for detailed blending of styles. You can combine multiple text prompts, style information from an uploaded image, and several LoRAs to create highly specific artistic styles that are hard to get with a single prompt.
• Advanced Video Generation: ComfyUI is the standard for advanced AI video. Its system is perfect for loading motion models, scheduling prompt changes over time, and applying other video effects, giving you a level of control that other UIs can't match.

Part 5: How to Choose the Right AI Image Tool

The goal is not to find the single "best" tool, but to build a toolkit for your specific needs.

Choose a Tool Based on Your Goal

• If you want to create... Fine Art / Concept Art / Artistic Inspiration:
  • Use Midjourney. It is positioned as the "Artist" with the best artistic and cinematic quality.
• If you want to create... A Photorealistic Image:
  • Use Midjourney for its cinematic realism or Google Imagen 4 for its high-resolution detail.
• If you want to create... A Marketing Ad / Logo / UI Mockup with Text:
  • Use GPT-4o or Google Imagen 4. They have the best text generation for commercial use. Ideogram is also a top specialist for this task.
• If you want to create... A Consistent Character in a Specific Pose:
  • Use Stable Diffusion (with LoRAs and ControlNet). This is the only reliable way to do this. Use a Character LoRA for the look and a ControlNet (OpenPose) model for the pose.
• If you want to create... An Edited / Enhanced version of an Existing Photo:
  • Use Adobe Photoshop (with Firefly). Its "Generative Fill" and "Generative Expand" features are designed for exactly this kind of editing work.
• If you want to create... An image in an Anime / Specific Niche Art Style:
  • Use Stable Diffusion (with a Style LoRA). The Stable Diffusion community has a huge library of LoRAs trained on specific styles (like "Ghibli style"), giving you the most control.

Choose a Tool Based on Your Skill Level

• If you are an... Absolute Beginner ("I just want to make cool pictures easily."):
  • Start with Midjourney or ChatGPT (GPT-4o). Their web interfaces are easy to use and give high-quality results without a steep learning curve.
• If you are a... Creative Professional ("I'm comfortable with Photoshop."):
  • Use the "Midjourney to Photoshop" workflow. This uses your existing skills and combines the best art generator (Midjourney) with the best professional editor (Adobe).
• If you are a... Power User / Tinkerer ("I'm willing to get my hands dirty."):
  • Install Stable Diffusion with the Automatic1111 UI. A1111 is the more beginner-friendly of the two main UIs and is perfect for learning and experimenting.
• If you are a... Developer / Automation Expert ("I want to build custom pipelines."):
  • Use Stable Diffusion with ComfyUI for building automated local workflows, or the OpenAI / Google Vertex AI APIs for commercial products. ComfyUI's node system is the best tool for automation.

Feature Showdown & Exclusion Rules

Feature Comparison: Text, Photorealism, and Prompt Following

Rules for Choosing a Tool

• If you absolutely need accurate text in your image, do not use Midjourney. Prioritize GPT-4o, Ideogram, or Google Imagen 4.
• If you must run the model on your own computer for privacy, cost, or to avoid filters, Stable Diffusion is your only option.
• If you are creating images for a large company and need a guarantee they are commercially safe from copyright claims, Adobe Firefly is the safest choice because of its "clean" training data.
• If you need to automate image generation with an API for a product, you must use the official OpenAI or Google APIs. Trying to automate Midjourney violates its rules and can get you banned.

Final Recommendations & Future Outlook

The era of looking for one "best" AI image tool is over. The expert user in 2025 uses multiple platforms and builds a strategic toolkit.

A recommended Power User's Toolkit for 2025 includes:

1. A Midjourney subscription for artistic ideation and creating beautiful base images.
2. An OpenAI ChatGPT Plus subscription for practical tasks, conversational editing, and images that need precise text or logic.
3. A local installation of Stable Diffusion with ComfyUI for total control, automation, video, and using specialized community-built models.
4. An Adobe Creative Cloud subscription if your work is already based in Photoshop, to bridge the gap for professional editing.

Looking ahead, the market will continue to evolve. The lines between "Artists" and "Collaborators" will likely blur as Midjourney is forced to improve its utility features and OpenAI and Google improve their artistic quality.

The next big change is already on the horizon: high-quality, controllable generative video and 3D models, a race where all the major companies are now competing. The skills learned in the image world will be the foundation for mastering these next-generation tools.