DEV Community: Neo Dong

Nano Banana 2.1 Review: Better Design, Cheaper Images—But Should You Switch?

Neo Dong — Thu, 08 Oct 2026 03:34:32 +0000

By NEO

An AI image can look impressive and still be useless for the job you need it to do. The headline is wrong, the product changes between versions, or a background edit quietly changes the person you wanted to keep.

That is the lens I’m using for this Nano Banana 2.1 review: does the update look more useful for actual creative work?

My take is that its most interesting improvements are design composition, selective editing, and reuse of existing subjects. Lower image output costs make those improvements easier to explore, but the pricing deserves a closer look before calling everything “half price.”

This is an analysis of the published examples and documentation, informed by two launch articles shared with me. I have not run an independent generation benchmark. The distinction matters when deciding how much confidence to place in a polished example.

My Take on Nano Banana 2.1

I would put Nano Banana 2.1 on the shortlist for campaign concepts, product variations, and image editing. I would be more cautious about long text layouts or work that depends on every identity detail surviving multiple revisions.

Google lists improvements in visual quality, text rendering, and multi-image fusion, alongside 1K, 2K, and 4K output. The model ID is gemini-nano-banana-2.1. Its supported reference inputs include up to 14 images, with consistency capabilities covering up to four characters and ten objects. Google’s model documentation.

Those features create a useful evaluation question: can you give the model a real brief and existing assets, then get a usable starting point without rebuilding the composition afterward?

That is more valuable to me than another isolated image that looks great in a launch announcement.

The Biggest Upgrade Is Design, Not Just Image Quality

The poster examples show why layout matters

Look at the two posters above. The desert layout uses large stacked lettering, small supporting labels, and a circular scene. The travel poster places a person in front of the headline, creating depth without abandoning the message.

What stands out is the relationship between the elements. The pictures, typography, and secondary details have distinct roles, rather than competing for equal attention.

For a marketing brief, that is the right direction. A viewer should understand the main message before stopping to read the smaller copy.

The studio, bucket-hat, and architecture examples make the same point in different formats. They invite questions about hierarchy and composition, rather than just texture or photographic realism.

I would still inspect every word before using an output. A successful short headline is not evidence that a whole page of small copy will remain accurate.

A beautiful image still needs a purpose

The motel staircase example is visually compelling: yellow railings, a pink wall, a green dress, and strong shadows give it a clear structure.

As a creative reference, it is useful. As a campaign asset, I would ask whether the scene leaves room for the required message and whether its visual tone fits the product.

That is how I would approach the model: start with a brief, not a request to make something vaguely cinematic. State the format, focal point, exact text, and where the composition needs breathing room.

For example, a brief could request a vertical product poster with one short headline, a product centered in the lower half, and a quiet upper area for copy. This is a suggested test brief, not a prompt I have validated.

Mask Editing Looks More Useful for Real Work

The dandelion example is the clearest illustration of why editing deserves attention. A marked subject becomes the anchor while its surroundings change.

The practical appeal is straightforward. Once you have a subject you like, replacing its background should not require starting from scratch.

For a product campaign, the equivalent might be preserving the item while trying a summer setting, a minimal studio scene, and a holiday background. The value depends on keeping the item recognizable across those changes.

My first check would therefore be the preserved area, not the new background. I would compare its shape, scale, edges, markings, and position against the original.

Google’s reported mask/ink editing score rises from 965 for Nano Banana 2 to 1049 for Nano Banana 2.1 with Thinking. This is a preference benchmark, not a promise of perfect edits. Google DeepMind’s model card.

I see this as a reason to test selective editing on a real asset. I would not treat the displayed examples as proof that the model follows every boundary in every attempt.

Subject Consistency Is Where I See the Most Practical Value

Product assets can become reusable starting points

The peach-colored bag example shows the same product presented in different environments. The display changes, while the bag remains the visual focus.

This is the capability I would examine first for ecommerce. A business already has product photos; the interesting question is how far those photos can travel into new compositions.

I would compare the strap, closure, silhouette, color, and material before accepting any variation. An attractive image of a slightly different bag is a failed product asset, even if the background looks excellent.

For my own evaluation, I would choose one item with distinctive details and ask for three contrasting settings. Keeping the product reference and requirements fixed would make drift easier to spot.

More references create more things to check

The group-fashion example is more ambitious. It combines multiple people into one composition, with different placements, poses, and relationships to the set.

The reference-image allowance should not be confused with a guarantee that fourteen distinct people retain their identities. Input capacity and consistency are separate claims.

In Google’s evaluation, multi-character consistency scores 1106 for Nano Banana 2.1 with Thinking, versus 978 for Nano Banana 2. That supports taking the improvement seriously, while still checking faces, clothing, and proportions individually. Model card.

My preference would be to start with fewer subjects and build complexity gradually. A successful two-person composition gives you a clearer baseline than a crowded first attempt where several things can go wrong at once.

The Pricing Cut Needs a Closer Look

The phrase “half the price” is appealing, but I would separate image output from the full request bill.

Here is Google’s listed Standard API pricing as checked on October 8, 2026:

Output resolution	Nano Banana 2 image output	Nano Banana 2.1 image output
1K	$0.067	$0.0336
2K	$0.101	$0.0504
4K	$0.151	Approximately $0.113

The 1K and 2K figures are roughly halved. The current 4K figure represents about a 25% reduction. Both supplied articles quote $0.0756 for 4K, but I am using the current official listing. Input is $1.50 per million tokens; text and Thinking output is $7.50 per million. Gemini API pricing.

These are Google API figures, not ReelDance credit prices.

I would measure cost per accepted asset

Suppose you need one approved product image. Your cost depends on how many attempts you discard, how much editing you request, and the review work required afterward.

A lower output price helps, but an image that needs three more revisions can erase part of that saving. A more expensive request can also be worthwhile if it gets the composition right sooner.

I would track four things during a small trial: attempts, total spend, correction time, and accepted outputs. Dividing the total by the accepted outputs gives a more useful business measure than the price of a single generation.

That is a proposed evaluation method, not a result from testing this model.

What These Examples Still Don’t Prove

Launch examples show what is possible. They do not tell us how many attempts produced those examples, how long they took, or how reliably another brief will behave.

The model card acknowledges problems with small text, long paragraphs, character consistency, partial editing instructions, and spatial placement. It also notes possible slowness or timeouts. Known limitations.

For me, that means three things before delivery:

Read the actual words, including small labels and numbers.
Compare retained subjects with their references at full size.
Check spatial relationships and factual content separately from visual polish.

Google also documents Web and Image Search grounding. I would treat it as a useful input to factual image generation, not a substitute for checking a finished diagram. Model documentation.

A beautiful infographic can make an error harder to notice. For an educational or technical asset, I would verify the information before approving the design.

Who I’d Recommend It For—and Who Should Wait

Workflow	My recommendation	First thing to check
Marketing concepts	Worth a focused trial	Message hierarchy and exact short copy
Product scene variations	A promising use case	Product details retained from the reference
Recurring characters	Test before committing	Identity across multiple revisions
Dense text layouts	Keep a separate typesetting step	Small text and long paragraphs
Factual diagrams	Use with editorial review	Labels, quantities, and relationships
API production workloads	Run a controlled comparison	Accepted-output cost and failure handling

I would start with an existing task where the current workflow has a specific weakness. If your problem is inconsistent product details, test that. If it is headline placement, test that instead.

Changing every part of the brief between models makes the comparison harder to interpret. Keep the references, required copy, output format, and acceptance criteria as consistent as the interfaces allow.

For developers, I would also avoid rushing a migration around an unverified deadline. As of this review, Google’s deprecation table recommends Nano Banana 2.1 as the replacement for gemini-3.1-flash-image, but lists no announced shutdown date for that model. Deprecation schedule.

My Verdict: Worth Trying, Not an Automatic Replacement

What interests me most is whether Nano Banana 2.1 can reduce the distance between a brief and an asset worth refining.

The posters make a case for stronger composition. The editing and product examples suggest more useful control over existing material. The pricing makes 1K and 2K exploration cheaper at the image-output level.

Those are good reasons to try it. They are not enough to declare it the winner for every image task.

My recommendation is a small, repeatable comparison using your own assets. Judge the model by the parts of your workflow that are expensive or frustrating today, then decide whether its improvements actually help.

Nano Banana 2.1 Review FAQ

Is Nano Banana 2.1 better than Nano Banana 2?

Google reports improvements in several design and editing evaluations. I would use that as a reason to compare the models on your own task, rather than assume the newer model wins every individual generation. Model card.

Is Nano Banana 2.1 half the price?

Its listed 1K and 2K image output charges are roughly half those of Nano Banana 2. The current 4K charge is not. Total request costs also include other billed components. API pricing.

How many reference images can it use?

Google lists up to 14 reference images. That does not mean fourteen people will all retain perfect identity in every result. Model documentation.

Has NEO independently tested the model?

Not for this article. This review analyzes published examples and verified documentation; it does not claim original generation results or measured success rates.

Try Nano Banana 2.1 on ReelDance

Nano Banana 2.1 is now available on ReelDance. If you want to see how it handles your own creative brief, try Nano Banana 2.1 on ReelDance. Start with one image you care about—a product scene, a poster, or a background edit—and judge the result against what you actually need to deliver.

Best Nano Banana 2.1 Image Generators in 2026: 5 Platforms Compared

Neo Dong — Wed, 07 Oct 2026 16:23:26 +0000

This article was drafted with AI assistance and reviewed and approved for publication. The publisher owns and builds ReelDance, and platform recommendations are based on documented workflows rather than a paid comparative image-quality benchmark.

Choosing the best Nano Banana 2.1 image generator in 2026 comes down to how smoothly you can move from creative ideas to completed visuals. Google designed Nano Banana 2.1 to support multi-image references, distinct 1K to 4K resolutions, and precise on-image text rendering. However, different web tools package these capabilities in very different ways.

For everyday creators, marketers, and visual designers, an integrated prompt library makes a decisive difference. ReelDance pairs a straightforward browser studio with a curated gallery of real prompt examples, giving you practical inspiration and direct controls in one place. In this guide, we compare five distinct platforms hosting Nano Banana 2.1 to help you find the right fit for your workflow.

Best Nano Banana 2.1 Image Generators in 2026 at a Glance

Each platform packages Nano Banana 2.1 for a different creative routine:

Platform	Best for	Why choose it	Cost or access
ReelDance	Marketing and poster designs	Prompt library plus browser studio controls	5 free welcome credits on signup
Gemini	Conversational drafting	Fast chat iteration in everyday dialogue	Google account access; features vary by tier
Google AI Studio	Model exploration	Direct testing with official 2.1 model identifier	Browser experimentation; API has separate billing
OpenArt	Style variations	Multi-image references with plain-text editing	Monthly credit subscriptions
Higgsfield	Multimedia campaigns	Supercomputer workspace with image and video tools	Tiered account subscriptions

What to Look for in a Nano Banana 2.1 Image Generator

Start by confirming that the platform explicitly names Nano Banana 2.1, or lists the official gemini-nano-banana-2.1 model identifier. Not every interface implements all native features, so verify the specific inputs and controls you need.

Next, check how the interface handles reference images and framing. The underlying model can accept up to 14 reference inputs, but tools present these differently. Look for direct choices between square, vertical, and widescreen formats rather than a fixed aspect ratio.

Finally, consider workflow support such as curated prompt libraries. Having accessible prompt collections lets you study real examples, layout structures, and phrasing patterns before generating, helping you refine your concepts and craft more effective prompts.

The 5 Platforms Compared

Each of the five platforms addresses a distinct type of user, from everyday content creators to backend software developers. Here is how their workflows operate across practical creative tasks.

1. ReelDance — Best for Everyday Creative Work

For designers, marketers, and content creators who want a dependable browser tool, ReelDance is our top recommendation for working with Nano Banana 2.1. The interface provides direct creative controls on the web without requiring a Google Cloud project or API billing setup. You can write a creative brief, set your framing, and manage your image requests directly in the studio.

ReelDance stands out by combining its generator with an extensive Nano Banana 2.1 Prompts library. Instead of guessing how to describe lighting or typography, you can browse real creator examples across categories like posters, products, and graphic styles. Each entry displays its full prompt structure and lets you transfer the text directly into the studio, making it much easier to start new creative projects.

Within the generator, you can select resolutions from 1K up to 4K, request batches of 1 to 4 images, and choose aspect ratios such as 1:1, 4:5, 9:16, 16:9, or panoramic formats. New accounts receive 5 free welcome credits upon registration. This starting balance allows you to immediately explore the interface, test studio settings, browse curated prompt examples across the library, copy phrasing patterns, and prepare your creative concepts before launching generations.

ReelDance also hosts dedicated video generation tools directly on the same platform, providing creators with a versatile unified creative workspace for broader visual marketing campaigns.

2. Gemini — Image Creation in a Conversation

Google offers direct conversational image creation through the Gemini web application. You can describe an image concept in natural language, review the output, and refine details with follow-up messages.

The main benefit of Gemini is its interactive drafting workflow. Creators can upload sketches or photo references directly into the chat and ask the model to adjust mood, lighting, or background elements organically. This dialogue-driven approach works well for creative brainstorming.

However, available generation features and active model options depend on your Google account tier, as noted in Google's Gemini help documentation. Because settings vary by account, creators seeking a structured studio interface with visible batch quotes often prefer a dedicated platform.

3. Google AI Studio — Model Exploration and API Workflows

For prompt experimentation, Google AI Studio provides a web-based testing space where users can try the official gemini-nano-banana-2.1 model directly. You can test text prompts in the browser without writing code.

However, programmatic development through the Gemini API operates under different rules. According to Google's API pricing documentation, the native 2.1 API has no free tier, charging per token for image generation, text, and optional thinking outputs. While developers need API credentials and billing projects for backend applications, creators looking for quick creative production will find managed browser studios far easier to navigate.

4. OpenArt — Reference-Based Image Variations

OpenArt incorporates Nano Banana 2.1 into an established creative platform designed for digital artists, concept illustrators, and visual designers. The system highlights reference-guided generation workflows, allowing creators to upload up to 14 source images to guide artistic styles, character attributes, and product details. Within the interface, users can configure resolutions up to 4K, choose framing dimensions, and apply text instructions to adjust existing visual concepts.

This structured setup provides practical utility for creative teams and independent illustrators who frequently build multi-image variations around established mood boards or visual asset collections. Access to the generation features is managed through monthly subscription plans detailed on the OpenArt pricing page, which distribute recurring credits for ongoing rendering tasks. While the multi-reference tooling offers substantial creative flexibility, designers should monitor their recurring credit balance when producing extensive batches of high-resolution visual assets.

5. Higgsfield — A Broader Creative Workspace

Higgsfield provides access to Nano Banana 2.1 through its expansive creative media platform, routing registered users directly into its dedicated Supercomputer interface. The environment integrates the 2.1 model alongside an extensive catalog of video generation tools, advertising design utilities, and multi-asset production workflows. Creators can supply up to 14 reference images and render detailed visual concept assets at resolutions reaching 4K for commercial marketing and social media campaigns.

This unified multimedia approach appeals to video producers, commercial agencies, and advertising teams who require a single workspace spanning both still concept art and animated motion assets. The platform operates on tiered commercial membership packages detailed on the Higgsfield pricing page, which users should review to understand available plan options and feature entitlements. Because the interface is structured around a broad production suite, creators seeking a simple, dedicated image tool may encounter more navigational complexity than necessary.

How ReelDance Combines a Prompt Library with Image Generation

A key advantage of ReelDance is its integrated Nano Banana 2.1 Prompts library. Instead of starting from an empty text box, creators can explore diverse categories like posters, products, art styles, and visual storyboards. Each card displays an attributed image preview that links to the complete original prompt text on its detail page, showing how specific descriptive phrasing guides the model.

Opening a prompt card reveals its full text, creator attribution, and source link. For example, the Viennese café chalkboard menu prompt, credited to creator Emilio (@EmilioSchwaiger), demonstrates how to describe an outdoor chalkboard menu with exact handwritten lettering and morning light. Studying this setup shows how to balance lighting, typography, and environmental details for your own briefs.

The detail page provides a "Copy prompt" button and a "Try this prompt" option that opens a prefilled studio draft. This action sets up your text and model selection without triggering an automatic paid generation, giving you time to edit. Because community prompts are often detailed, you can shorten or customize the text to fit your brand.

These gallery images illustrate effective prompting techniques with proper creator credit and original links, rather than serving as commercial stock assets. By adapting these structural patterns to your own products, subjects, and layouts, you can launch new generation drafts with greater confidence in a single browser workflow.

Which Platform Fits Your Workflow?

For everyday creators, marketers, and poster designers, ReelDance is our top recommendation. Combining an accessible prompt library with direct framing controls and upfront credit quotes lets you move smoothly from inspiration to finished visuals without configuring developer keys.

Other platforms fit different priorities. Gemini suits casual conversational brainstorming in chat. Google AI Studio serves users testing model parameters or planning API integrations. OpenArt works well for multi-image style variations, while Higgsfield supports production teams managing broader multimedia and video suites.

Step-by-Step: From Prompt Example to Finished Image on ReelDance

Here is how to create images on ReelDance using a prompt library example:

Find a prompt example. Browse the categorized Nano Banana 2.1 Prompts library to locate a layout, subject theme, or lighting style that matches your goal. Click into a detail card to inspect its exact phrasing and creator notes.
Copy and adapt the brief. Use "Try this prompt" to load a studio draft, or copy the text directly into the Nano Banana 2.1 Image Generator. Replace subjects and branding with your own details. For example, a beverage brand could propose:

"Solstice Botanical Elixir" embossed on an amber glass bottle, resting on a sunlit limestone plinth, surrounded by fresh eucalyptus leaves and wild citrus slices, soft morning light, editorial product photography

Select your settings. Ensure Nano Banana 2.1 is selected. Choose your aspect ratio, such as 4:5 for mobile feeds or 16:9 for banners, pick an output resolution from 1K to 4K, and set your image count.
Claim your welcome credits and prepare prompts. Register an account to receive 5 free welcome credits to explore the platform. You can freely browse the prompt library, copy established prompt structures, and refine your ideas before submitting generation tasks.
Generate and inspect. Submit your request and review the returned visuals for composition, lighting, and typography accuracy. For deeper model guidance, check our guides on What Is Nano Banana 2.1? and Nano Banana 2.1 vs Nano Banana 2.

Explore the Nano Banana 2.1 Prompts library to find inspiration, claim your 5 welcome credits, and start creating on the Nano Banana 2.1 Image Generator today. Select your framing and bring your creative concepts to life.

Frequently Asked Questions

Is Nano Banana 2.1 available?

Yes. Following Google's October 2026 documentation updates, Nano Banana 2.1 is accessible through the Gemini consumer web app and Google AI Studio for prototyping. Creative platforms including ReelDance, OpenArt, and Higgsfield also provide direct access to the model within their creation interfaces.

Which Nano Banana version is best?

The ideal version depends on your project requirements rather than an absolute ranking. While 2.1 incorporates Google's latest model refinements, older versions still suit established workflows. Evaluate options by practical factors, such as intuitive studio controls, flexible resolutions, or curated prompt library support on ReelDance.

Is Nano Banana 2.1 better than Nano Banana 2?

Google documents notable improvements in visual fidelity, typography layout, and instruction adherence in 2.1 over Nano Banana 2, though individual results vary. To decide for your workflow, compare both models using identical prompts and aspect ratios to evaluate text precision and composition directly.

How can I get started with Nano Banana 2.1 for free?

On ReelDance, you receive 5 free welcome credits when registering a new account. You can freely explore the platform, browse creative prompt examples across the library, copy phrasing structures, and prepare your draft concepts directly inside the studio interface before generating.

Nano Banana 2.1: What Changes for Design, Editing, and Image Costs

Neo Dong — Wed, 07 Oct 2026 13:01:29 +0000

Better text, more controlled edits, and a lower image bill—with an important catch at 4K.

By Neo Dong · Founder of ReelDance

Drafted with AI assistance using official documentation and announcements.

An original AI editorial illustration accompanying this Nano Banana 2.1 story.

When I build creative tools, three things matter to me: an image that follows a brief, readable words, and its bill. In artificial intelligence, practical tools matter more than flashy promises. Google's release of gemini-nano-banana-2.1 brings welcome updates to each of these areas.

Readable Text and Cleaner Layouts

In design, my priority is clean text. If a poster has wrong words, it needs fixing before anyone can use the graphic.

According to Google's documentation, gemini-nano-banana-2.1 improves text and infographic layouts. For wide display graphics and banners, the documentation confirms support for panoramic ratios: 1:4, 4:1, 1:8, and 8:1. Google reports that it fixed stitching artifacts that previously disrupted 2K and 4K panoramic outputs.

I recommend describing exact text placement. Here is a prompt I propose:

A minimalist exhibition poster with bold sans-serif text reading 'SUMMER SALON' centered at the top, a smaller subhead 'Gallery B', and a ceramic vase standing in front of the letters.

Watching how models align text and objects shows whether an image tool can follow a real design brief.

Editing Parts of an Image

Most image projects do not finish on the first attempt. You might love a product shot, but need to move it from a studio table to an outdoor patio. Starting over from scratch wastes time and gives you an entirely different product.

According to Google's image generation guide, Nano Banana 2.1 supports conversational editing. You can ask the model in plain language to change one part of an image while leaving the rest in place. For example, you can keep a perfume bottle or a sneaker exactly where it stands and ask for a sunny park background instead of a grey studio wall.

My advice when asking for background swaps is to always zoom in on your subject. Check product outlines, brand logos, and fine edges. Even with conversational editing, small shifts can happen around fine details. Knowing where to look helps you catch errors early.

Keeping Characters and Objects Consistent

For storyboards and marketing campaigns, keeping the same subject across different scenes is critical. If your main character wears different clothes or changes their face in panel two, the story breaks down.

Google's documentation states that Nano Banana 2.1 supports up to 14 reference images in a single request. The model maintains consistency for up to 4 characters and up to 10 objects across those references, without a rigid split between people and items.

I recommend uploading clear photos of your product from different angles when you build a new scene. Giving the model useful reference views helps it follow your subject across images.

Graphic Layouts Across Modern Tools

This emphasis on clean text and structured layout is spreading across modern creative workflows. When OpenAI introduced ChatGPT Images 2.5, its announcement highlighted similar priorities: legible typography, conversational image editing, and consistent character details across revisions. For me, seeing multiple platforms focus on legible lettering and dependable revisions validates what matters most in practical production. Creators need tools that reliably follow exact instructions without forcing designers to start completely from scratch.

Understanding the New Pricing Schedule

Under Google's developer pricing, tokens are the billing units used to count API use. Image output fees for 1K and 2K halve compared to Nano Banana 2. At 4K, output uses 3,780 tokens instead of 2,520, so the image output fee drops by 25%.

Because prices for input prompts and thinking tokens increased, your final bill depends on your entire prompt history, not just the image fee.

Pricing Metric	Nano Banana 2.1	Nano Banana 2	Nano Banana Pro	GPT Image 2 (Launch Reference)
Text Input ($/1M tokens)	$1.50	$0.50	$2.00	$5.00
Image Input ($/1M tokens)	$1.50	$0.50	$2.00	$8.00
Text / Thinking Output ($/1M tokens)	$7.50	$3.00	$12.00	Not comparable*
Image Output ($/1M tokens)	$30.00	$60.00	$120.00	$30.00
1K Image Output Fee	$0.0336	$0.0672	$0.134	Varies by size and quality
2K Image Output Fee	$0.0504	$0.1008	$0.134	Varies by size and quality
4K Image Output Fee	$0.1134	$0.1512	$0.240	Varies by size and quality

Rates from Google standard API pricing. GPT Image 2 uses April 21, 2026 launch rates with text billed separately. Nano Banana Pro per-image rates reflect Google's published schedule.

Rollout Across Google Services

Google announced the release on X, and a follow-up reply confirmed that the model is rolling out across seven surfaces: the Gemini app, AI Mode in Search, Google AI Studio, Google Flow, Stitch, Google Ads, and the Gemini Enterprise Platform.

Try Nano Banana 2.1 on ReelDance

When I choose an image model, my priorities are clear text, predictable costs, and dependable layouts. When a tool delivers on those basics, it makes sense to pick it for creative projects.

We have added Nano Banana 2.1 to the image generator on ReelDance. You can start using it right away:

Open ReelDance and click Image Generator.
Select Nano Banana 2.1 from the model dropdown.
Write your prompt describing your scene and text.
Choose your aspect ratio and resolution.
Check the displayed credit cost and click generate.

Give the new model a try on your next project and see how it fits your workflow.

Sources

Google Gemini API: Nano Banana 2.1 Documentation
Google Gemini API: Image Generation Guide
Google Gemini API: Developer Pricing
Google Official Announcement on X
Google Rollout Surfaces Post on X
OpenAI: Introducing ChatGPT Images 2.5
OpenAI Developer Community: Introducing GPT Image 2

About the Author

Neo Dong is the founder of ReelDance and specializes in AI video generation products. He brings years of experience building AIGC products, with a focus on practical creative workflows.