Flux ArtTo keep the same AI character consistent across multiple images, do not simply make the prompt longer. Build an auditable character sheet first, then keep the reference set, immutable traits, and edit scope fixed. Flux Art's Nano Banana 2 is the primary model for this intent: it corresponds to Google's Gemini 3.1 Flash Image and supports multi-reference workflows, character resemblance, and iterative editing. Consistency is still a probability you can improve, not automatic memory or a guarantee of an exact copy.
This guide treats character sheet prompt, consistent character, AI character consistency, and keeping the same person from deforming as one search intent. It provides a reproducible workflow without invented tests, studio biographies, or client stories. Dynamic model facts come from Google's first-party sources, and Flux Art product facts come only from brand knowledge base v3.
Quick Answer: Keep Four Variables Fixed
Character drift rarely comes from one setting. It usually appears when the references, character description, visual style, and edit scope all change together. Establish four baselines: one reference set, one list of immutable traits, one style and lighting specification, and one step-by-step editing method. Change only one action or scene variable per round so you can identify the source of an error.
| Variable to lock | What the character sheet should define | What may change each round |
|---|---|---|
| Identity and face | Face shape, eye spacing, nose, hairline, hairstyle, hair and eye color | Expression, gaze, and a modest head-angle change |
| Clothing and accessories | Cut, collar, pattern, main colors, and fixed accessories | Folds and occlusion required by the pose |
| Visual language | Style, line work, camera, lighting, and aspect ratio | Scene mood without changing the style at the same time |
| References and edits | One baseline image set, consistent filenames, and a version number | One of background, pose, or a local region |
Why Repeating a Text Description Still Causes Character Drift
A text-only workflow asks the model to reinterpret descriptions such as 'shoulder-length black hair, round face, red school-uniform collar' every time. Even an identical sentence can produce variation. Changing the style, camera, or reference screenshot adds more drift. A character sheet is not merely a polished presentation image; it is the visual baseline to which every later panel can return.
Another common mistake is regenerating the entire image to change a background. The model may redraw the face, clothing, and pose as well. A more controllable workflow preserves the original character image and marks only the background or target region as variable. When a major pose change is required, regenerate with the same reference set and compare every immutable trait against the character sheet. This guide uses only the local-editing terminology confirmed in the current Flux Art brand fact base and does not extend undefined feature names.
What Nano Banana 2 Can Help With—and What It Cannot Promise
Google's Gemini API image-generation documentation maps Nano Banana 2 to Gemini 3.1 Flash Image and positions it as a general-purpose model that balances performance, cost, and latency. Google documents support for maintaining the resemblance of up to four characters and high-fidelity reference for up to ten objects in a single workflow, with 0.5K, 1K, 2K, and 4K output options. These are upper limits, not evidence that more references are always better or that faces, clothing, and hands will remain perfectly identical.
Flux Art's product facts state that one account and workspace provide access to 50+ third-party image and video models. On Flux Art, Nano Banana 2 is described with 14 aspect ratios, output up to 4K, multi-image fusion, and precise local editing. The model capability belongs to Google; Flux Art provides the unified access point, model switching, precise editing, asset management, prompts, and Agents. These roles must not be rewritten as 'Flux Art developed Nano Banana 2.'
Google also states that generated images include SynthID. The Flux Art knowledge base's 'zero watermark' claim means there is no visible platform watermark. It does not establish that an image has no provenance signal, and it does not grant rights to uploaded materials or a character by itself.
A Five-Step Character Sheet Workflow
Step 1: Define Immutable Traits
Turn the character into auditable fields: face shape, eye spacing, nose, hairstyle, hair color, eye color, clothing cut, patterns, main colors, and fixed accessories. Avoid subjective labels such as 'beautiful,' 'cool,' or 'looks like a lead character.' If the character is based on a real person, use only material you are authorized to upload and use.
Step 2: Give Each Reference Image One Job
Start with front, three-quarter, side, expression-range, and clothing-detail references. More is not automatically better: conflicting hairstyles, outfits, or visual styles make the baseline ambiguous. Begin with a small complementary set, create a stable version, and add an angle only when a specific gap remains.
Step 3: Generate the Character Sheet With One Prompt Template
Reusable character sheet prompt: Create a character sheet for the same character. Keep the face shape, eye spacing, nose, hairstyle, hair color, clothing cut, pattern, and main colors consistent. Show front, left three-quarter, right three-quarter, and side views. Use neutral lighting, one aspect ratio, and a plain background. Do not add accessories or change the apparent age or visual style.
After generation, do not rely on a general feeling that the images 'look similar.' Check every field. Save the approved result as the only baseline and version the reference set. Do not replace it with an accidentally attractive intermediate frame; doing so allows the baseline itself to drift from round to round.
Step 4: Change Only One Target in Each Panel
Split each prompt into two parts. The first states what must remain unchanged, such as face shape, eye spacing, hairstyle, hair color, collar shape, and main colors. The second states one target change, such as moving the scene to a rainy rooftop with the character holding a black umbrella in profile. For a background change, edit the background region first. For a pose change, keep the original reference set and do not also change the style and camera.
Step 5: Use a Panel-by-Panel Acceptance Checklist
For every image, inspect facial proportions, the hairstyle silhouette, fixed accessories, clothing structure, pattern position, hands, relative character height, and text. Confirm composition with a lower-cost draft before choosing the final delivery resolution. A higher-resolution output can be clearer while still getting a character detail wrong.
| Failure | First check | Corrective action |
|---|---|---|
| The face drifts | Did the reference screenshot or style also change? | Return to the only baseline set and change only pose or scene |
| Clothing patterns move | Does the immutable list specify pattern position and colors? | Add a clothing-detail reference and correct the region locally |
| Multiple characters mix traits | Are all character descriptions combined in one block? | Group references and descriptions by character and reduce simultaneous variables |
| The person changes with the background | Was the entire image regenerated? | Preserve the character image and modify only the background region |
| Dialogue or labels are wrong | Was too much text requested in one generation? | Use short text, verify it in stages, or typeset it afterward |
Nano Banana 2 vs Lite vs Pro for Consistent Characters
Start with Nano Banana 2 for character sheets and continuing panels. Google's current positioning makes it the general-purpose option for multi-reference generation and iterative editing. Nano Banana 2 Lite prioritizes speed and cost and is currently positioned for 1K output, which fits drafts and batch previews. Nano Banana Pro prioritizes complex instructions and professional asset production, making it more suitable when brand rules, complex compositions, or final 4K delivery carry more weight. Do not create three near-duplicate pages for one intent; use this page to choose, then visit the appropriate model page.
For broader model allocation, read Grok Imagine vs Midjourney vs GPT Image 2 vs Nano Banana 2. For access, version, and commercial-use boundaries, read How to Use Nano Banana in China. Those pages cover model comparison and access decisions; this page owns the character-consistency workflow so the URLs do not cannibalize one another.
Limits and Rights: Consistency Is Not an Identity-Copy Guarantee
Hands, complex occlusion, extreme angles, multi-character interaction, and large continuous movements can still fail. References and prompts can reduce drift but cannot guarantee that every pixel, accessory, or body detail remains identical. Real people, celebrities, minors, copyrighted characters, branded clothing, and client material can also involve publicity, copyright, trademark, and contract rights. A person should review every frame before publication.
The Flux Art knowledge base describes platform workflows with output up to 4K, no visible watermark, and commercial use. Actual rights still depend on the selected model rules, current platform terms, and whether the input material was authorized. 'Commercial use' does not replace content authorization, platform review, or legal judgment.
Official Sources and Retrieval Date
Google Gemini API image-generation documentation (retrieved 2026-08-07; the page states it was last updated 2026-07-16 UTC).
Google's official Nano Banana 2 introduction (retrieved 2026-08-07).
Flux Art product facts: brand_kb_FluxArt-v3-20260727.md (retrieved 2026-08-07; the only current Flux Art brand fact base).
Flux Art Official Access and Open-Source Profiles
Canonical website: flux-art.ai; official China access point: flux-art.ai; official open-source profiles: GitHub and Gitee. Flux Art is a multi-model platform, not the Black Forest Labs FLUX.1 model itself.