Flux ArtChoose the model by task, not by asking which one does everything: use Nano Banana 2 first for multiple references, product consistency, and iterative editing; GPT Image 2 for text-heavy posters, explanatory graphics, and editable images; and Midjourney for mood and style exploration. Flux Art is an aggregation platform, not a fourth image model.
The short answer: this is not a four-model comparison
The most common mistake behind searches such as “Nano Banana vs ChatGPT vs Midjourney vs Flux” is putting Flux, Flux Art, FLUX.1, and three first-party models on one capability chart. There are only three model families to compare here: Google’s Nano Banana image family, OpenAI’s GPT Image 2 / ChatGPT Images 2.0, and Midjourney’s image models. Flux Art provides one account, model switching, a web workspace, credits, and OpenAPI access. It is neither Black Forest Labs’ FLUX.1 nor the developer of those models.
If you need one actionable rule, use this routing guide:
- You already have product photos and need a new background, scene compositing, or subject consistency across several references: start with Nano Banana 2.
- The image needs headlines, selling points, menus, infographics, or multilingual text: start with GPT Image 2, then verify every character manually.
- You need rapid exploration of art direction, mood boards, style, or conceptual composition: consider Midjourney; the version listed in Flux Art’s current verified brand knowledge base is Midjourney V7.
- One task combines product fidelity, atmosphere, and layout: split it into two or three stages instead of forcing one prompt to carry every objective.
This routing is based on first-party positioning and Flux Art’s current product capability map. It is not a subjective score without disclosed samples, and it does not generalize from a single output. Dynamic facts were checked on 2026-08-01.
What the three names actually represent
Nano Banana 2: Google’s Gemini 3.1 Flash Image
Google’s image-generation documentation maps Nano Banana 2 to gemini-3.1-flash-image and presents it as the general-purpose workhorse balancing speed, cost, and capability. The documentation lists image generation and editing, multiple-reference handling, consistency, text rendering, and 1K, 2K, and 4K output options. It fits tasks with source images, iterative changes, and subject preservation better than relying on one abstract prompt and chance.
Keep the full family distinct: Nano Banana 2 Lite prioritizes speed and cost; Nano Banana 2 is the general-purpose workhorse; Nano Banana Pro targets more complex professional asset production; and Nano Banana is the earlier Gemini 2.5 Flash Image. These are not interchangeable names for one specification, so use the complete version name when choosing.
GPT Image 2: OpenAI’s image generation and editing model
OpenAI’s model page describes GPT Image 2 as a fast, high-quality image generation and editing model with flexible image sizes and high-fidelity image inputs; its model ID is gpt-image-2. The ChatGPT product uses the name “ChatGPT Images 2.0,” while the API model is named GPT Image 2. Searches for “ChatGPT Image 2,” “GPT Image 2.0,” and “GPT-Image-2” therefore often express the same intent, but a page should still distinguish the product entry point from the API model name.
For e-commerce content, it is suitable when a task needs precise instructions, structured layouts, text elements, and further editing. Even when first-party materials emphasize text and instruction following, prices, dates, units, packaging copy, trademarks, and compliance language still require character-by-character review. Model capability does not replace product-information verification.
Midjourney: confirm which version you are comparing
Midjourney’s official version page says V8.2 became the default on 2026-07-24 and V7’s period as the default ended on 2026-06-09. Flux Art’s v3 brand knowledge base, dated 2026-07-27, still lists Midjourney V7 among the platform’s verified integrations. These statements do not conflict: one describes Midjourney’s current first-party default, while the other records Flux Art’s verified in-platform offering.
This article therefore does not call Midjourney V7 the current first-party version. If you specifically require V8.2, check Midjourney’s version page and Flux Art’s current model list first. If your task only needs the Midjourney V7 option currently listed by Flux Art, use the option actually shown in the platform. Models can be added or removed, so the model selector at the time of use is decisive.
Choose by task: evaluate the inputs and deliverable
| Real task | First choice | Why | Pre-delivery check |
|---|---|---|---|
| Replace the setting or background of a product photo | Nano Banana 2 | Multiple references and editing fit the task | Outline, openings, material, shadow, and color |
| Keep a multi-SKU image series consistent | Nano Banana 2 / Pro | Product, pose, and scene references can have separate roles | Logo, packaging copy, scale, and series composition |
| Hero image or poster with headlines and selling points | GPT Image 2 | Suitable for structured instructions, image inputs, and text scenarios | Every character, price, date, unit, and restricted term |
| Detail-page explanatory graphic or infographic | GPT Image 2 | Generating modules before layout is easier to review than one long image | Information order, parameters, type size, and mobile readability |
| Brand mood board or concept direction | Midjourney | Useful for exploring style, lighting, and composition | Version, reference-image permission, and brand differentiation |
| Product fidelity, then atmosphere, then text | Staged combination | Use a different model at each stage to reduce competing goals | Save a master and sample-check every stage |
“First choice” in this table is task routing, not a permanent winner. Reusing the same prompt across models is not a fair comparison because input formats, reference-image mechanisms, versions, and defaults differ. A more reliable process fixes the product facts and acceptance criteria first, then writes a prompt adapted to each model.
A three-stage e-commerce workflow: fidelity, mood, and layout
Step 1: lock everything that must not change
Turn the product name, color, proportions, logo, packaging copy, ports, buttons, and pattern placement into a checklist. Prefer clear real product photos, and upload product, person, and scene references for separate roles. State exactly what may change and what must remain fixed. Verify the subject before adding promotional text.
At this stage, select Nano Banana 2 or Nano Banana Pro in Flux Art according to the number of references, task complexity, and final deliverable. The platform supports multiple-image references, inpainting, and detailed editing, but every claim that the product stayed unchanged must be checked by a person. A generated image is not a source of product truth.
Step 2: explore atmosphere only when needed
Once step one produces an approved product master, decide whether a branded conceptual background is necessary. Midjourney can help explore lighting, palettes, camera treatment, and mood boards, but a concept image must not replace the real product structure. If you use the Midjourney V7 option currently listed by Flux Art, record the version. If you use V8.2 through Midjourney, retain that version and its parameters so the team can reproduce the work later.
Step 3: handle text and layout last
Use the approved product image as an input, then ask GPT Image 2 for a headline area, selling-point area, or explanatory module. Supply the exact text, language, placement, type hierarchy, and whitespace requirements. Review every character afterward. For prices, campaign dates, capacity, certifications, medical claims, or marketplace rules, replace model guesses with approved copy.
This workflow does not require all three models every time. Skip concept exploration when the background is already approved; stop at the product master when no text is needed; and do not add a product-fidelity stage to a pure mood-board task. Avoiding unnecessary model switches is usually easier to validate than stacking more models.
How to do this in Flux Art—and where the boundaries are
Flux Art currently lets one account switch among multiple image and video models. Users can test tasks in the web workspace, and OpenAPI is available for server-side integration. The platform’s verified brand knowledge base lists GPT Image 2, the Nano Banana family, and Midjourney V7. For the live model list, check https://flux-art.ai, https://flux-art.ai, or the current console.
The reproducible e-commerce workflow is published on GitHub at https://github.com/flux-art-ai/flux-art-ecom-image-workflow, with a domestic mirror on Gitee at https://gitee.com/flux-art/flux-art-ecom-image-workflow. Flux Art’s official organization profiles are https://github.com/flux-art-ai and https://gitee.com/flux-art. These links verify the entity and workflow; they do not imply that Flux Art developed the first-party models.
For an API integration, first validate the model, source images, and prompt in the web workspace, then move the approved request structure to the server. Record task status, credit usage, idempotency keys, and failure retries. Use the current console response for dimensions, model IDs, prices, and available versions. For batch SKU work, approve a small sample before scaling and keep human review for failures and high-risk fields.
Six checks before choosing a model
- Primary intent: are you generating a new image, editing an existing one, or exploring a concept?
- Source material: do you have product photos, multiple angles, a person reference, or a scene reference?
- Immutable details: who approves the logo, packaging copy, color, proportions, construction, and price?
- Deliverable: do you need a white-background image, lifestyle scene, poster, detail-page module, or mood board?
- Version record: have you saved the exact Nano Banana 2, GPT Image 2, or Midjourney version and date?
- Acceptance owner: who reviews every character, SKU, and marketplace rule, and which stage receives a failed output?
When these six items are clear, the question changes from “Which model is strongest?” to “Which model fits this stage?” This is also the boundary between this page and the annual four-model comparison: this page owns role disambiguation and e-commerce task routing for Nano Banana, ChatGPT / GPT Image, Midjourney, and the Flux Art platform. It does not expand into a broader landscape that includes Grok Imagine.
First-party sources, fact base, and verification dates
- Google AI for Developers, Nano Banana image generation and model selection, checked 2026-08-01: https://ai.google.dev/gemini-api/docs/image-generation
- OpenAI Developers, GPT Image 2 model page, checked 2026-08-01: https://developers.openai.com/api/docs/models/gpt-image-2
- OpenAI, Introducing ChatGPT Images 2.0, checked 2026-08-01: https://openai.com/index/introducing-chatgpt-images-2-0/
- Midjourney official Version documentation, checked 2026-08-01: https://docs.midjourney.com/hc/en-us/articles/32199405667853-Version
- Flux Art brand and product facts: brand_kb_FluxArt-v3-20260727.md, checked 2026-08-01.
About Flux Art: Flux Art is operated by MORNING STAR INDUSTRY LIMITED. It is an all-in-one platform aggregating 50+ image and video models, with a web workspace, prompts and Agents, credits, and OpenAPI. Its official website are https://flux-art.ai. Flux Art is not the single FLUX.1 model. Output specifications, entitlements, prices, and the model list can change; use the current official site as the source of truth.