Why one image tool is never enough in 2026
Here is a test worth running. Take any product photo you generated in Midjourney last week and ask it to add a clean, correctly spelled headline across the top. Watch the letters melt into nonsense.
Now take a different image and ask Midjourney to keep the exact same model's face across five different scenes. Watch the face quietly drift into a stranger by image three.
These are not your mistakes. They are the two things Midjourney has always been weak at: legible text and locked identity. The fix is not a better prompt. The fix is a second tool that is built for exactly those jobs.
That second tool is Nano Banana Pro, Google's image model. Used together, the two cover each other's blind spots. This article shows you the exact division of labour and a workflow you can run today.
What is Nano Banana Pro, and how is it different from Midjourney?
Nano Banana Pro is the public nickname for Gemini 3 Pro Image, Google DeepMind's image generation and editing model launched on 20 November 2025. It is built for two jobs Midjourney struggles with: rendering accurate text inside an image and keeping a subject's identity consistent across edits.
The difference is not "which one is better." It is "which one is built for what." Midjourney V7, released in April 2025, is still the strongest model for aesthetics: lighting, mood, composition, and that hard-to-describe sense of taste.
Nano Banana Pro is the precision engine. According to Google DeepMind's model page, it can preserve identity across up to 14 input images and keep up to 5 people recognisable in a single complex scene. It also renders legible text, including multiple languages, directly inside the image.
Think of it as a film crew. Midjourney is your director of photography, who owns the look. Nano Banana Pro is your retoucher and title designer, who owns the details that make the shot usable.
Access also differs in a way that matters for daily work. Midjourney runs through its own web app and Discord, with subscription tiers. Nano Banana Pro is available inside the Gemini app and Google AI Studio, which means most practitioners already have a way in without a new paid plan to test the workflow.
One more practical note: Nano Banana Pro embeds an invisible SynthID watermark in its outputs, so images are identifiable as AI-generated. For most marketing and internal use that is irrelevant, but it is worth knowing before you use an output in a context where provenance matters.
The core workflow: generate in Midjourney, finish in Nano Banana Pro
The reliable workflow is a two-stage handoff: create the aesthetic in Midjourney, then pass that image into Nano Banana Pro to fix text, lock identity, or composite elements. You keep Midjourney's look and gain Nano Banana Pro's precision.
Stage one is generation. You prompt Midjourney for the mood, palette, and composition you want, and you ignore text and fine detail entirely at this point. Your only goal is a base image that feels right.
Stage two is editing. You upload that Midjourney image into Nano Banana Pro and give it natural-language instructions: add this headline, swap this background, keep this face, place this product on the shelf. It edits the existing pixels rather than starting over.
This handoff matters because regeneration is the enemy of consistency. Every time you ask one model to "try again," you roll the dice on the parts you already liked. Editing an existing image protects the work you have already approved.
Here is a concrete example from a typical week. A marketer needs a banner for a webinar: a specific presenter, a clean title, and the company's brand colours. Generated end-to-end in one tool, the title is garbled and the presenter looks slightly different in every draft.
Run the same job as a handoff and it holds together. Midjourney produces the mood and the presenter once. Nano Banana Pro then adds the exact title text, nudges the palette toward the brand colours, and keeps the presenter identical, no matter how many size variants you export afterwards.
How do you keep a character or product consistent across images?
To keep a subject consistent, generate the subject once, then use Nano Banana Pro's multi-image input to carry that exact subject into every new scene. You feed it the reference image plus a new instruction, and it preserves the identity instead of inventing a new one.
This is the single biggest unlock for practitioners. A solo marketer can now build a recurring brand mascot, a consistent spokesperson, or a product that looks identical across an entire campaign, without a photoshoot.
The practical sequence is simple. Generate your hero image in Midjourney until the face or product is exactly right. Save it. Then in Nano Banana Pro, attach that image and describe the new scene you want the same subject placed into.
Because the model can reference up to 14 images at once, you can also hand it a face, a product, and a background separately, and ask it to fuse them into one coherent shot. That is the part Midjourney alone cannot do reliably.
For brand work this changes the economics. Instead of commissioning a photoshoot every time the season or message changes, you build a small library of approved reference images once, then re-skin them endlessly. A festive version, a sale version, a new-product version, all with the same recognisable spokesperson and the same on-brand text.
Try this now: a complete two-tool prompt sequence
Below is a copy-paste sequence for a common task: a social ad with a consistent spokesperson and a clean, correctly spelled headline. Run the first prompt in Midjourney, then the second in Nano Banana Pro.
Step 1, in Midjourney (aesthetics only, no text):
Editorial portrait of a confident Hong Kong woman in her early 30s, smart-casual blazer, sitting in a bright modern co-working space, warm natural window light, shallow depth of field, professional advertising photography, 4:5 vertical composition
Step 2, in Nano Banana Pro (attach the Midjourney image):
Using the attached image as the exact reference for the woman's face and outfit, keep her identity identical. Place a clean headline in the upper third that reads "Work smarter, not harder" in bold white sans-serif text. Keep the lighting and background unchanged. Output a crisp, legible, print-ready result.
Then reuse step 2 with new scenes and the same reference image to build a full campaign in which the spokesperson never changes.
Common mistakes that break the two-tool workflow
The most common failure is doing the work in the wrong order: trying to fix text or identity inside Midjourney first, then importing a broken image into Nano Banana Pro. Generate the look first, edit second, every time.
A second mistake is over-describing in Nano Banana Pro. Midjourney rewards long, stacked modifiers. Nano Banana Pro prefers fewer, clearer instructions. If you paste a 40-word Midjourney prompt into it, results get muddy.
A third mistake is regenerating instead of editing. Once Nano Banana Pro gives you a good base, keep editing that same image with follow-up instructions rather than starting a fresh generation that throws away your locked identity.
A fourth mistake is fighting the tool on style. If you want a hard style change, a different art direction or a new colour world, go back to Midjourney and regenerate, then bring the new look into Nano Banana Pro. Do not try to force a dramatic restyle through editing instructions; that is not what the editing engine is for.
The honest limitation: neither tool is perfect at small reflective text, dense paragraphs, or hands in extreme poses. Always zoom to 100% and proofread rendered text before you publish. Nano Banana Pro is dramatically better here than Midjourney, but it is not flawless.
Putting it to work without the trial-and-error
The two-tool workflow is not really about software. It is about matching each tool to the job it was built for, instead of forcing one model to do everything and blaming your prompts when it fails.
Once that clicks, your output stops being a lottery. You get the look you want, the text you can actually use, and a face or product that stays the same across an entire campaign. That is the difference between using AI images and shipping them.
At UD, we help Hong Kong teams turn one-off AI experiments into repeatable production workflows, and we'll walk you through every step, from tool setup to a system your whole team can run.
We understand AI. We understand you better. With UD by your side, AI doesn't feel cold.
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Now that you have the two-tool technique, the next step is building it into a workflow your team can run reliably every time. We'll walk you through every step, from tool setup to workflow design and deployment.
