Gemini Nano Banana 2.1 vs Gemini Omni 1.1 Flash: A Still and a Clip, Priced in Different Units

The first thing to know about comparing Nano Banana 2.1 with Omni 1.1 Flash is that they are not substitutes, and the pricing pages make that obvious in a way a feature list does not. Nano Banana 2.1 is billed in images — $30 per million image tokens, which the vendor resolves to $0.0336 for a 1K render. Omni 1.1 Flash is billed in seconds of video — $17.50 per million output video tokens, which a vendor footnote converts to roughly $0.10 per second of 720p. One is a workhorse still-image and editing model that reached general availability on October 6, 2026. The other is a video generator that the vendor's documentation tells developers to use as their default for video and to leave scene extension to Veo 3.1. Choosing between them is really a question about which half of a pipeline you have not built yet.

There is also a naming trap worth clearing up before any of the numbers. The model most people call Gemini Omni 1.1 Flash is listed by Google as Gemini Omni Flash; the "1.1" exists only in the endpoint, gemini-omni-1.1-flash. Nano Banana 2.1 has the opposite arrangement — its display name carries the version, and its endpoint matches at gemini-nano-banana-2.1. If you are reading a changelog or a billing export, that mismatch is the reason one of these is easy to find and the other is not.

The two jobs, stated plainly

Gemini Nano Banana 2.1 generates and edits still images conversationally. Its documented inputs are text, image and video in any combination — audio is not accepted — and it outputs text and images, with interleaved text-plus-image output configurable. It holds up to 14 reference images, split as up to 10 high-fidelity object references and up to 4 character references, and it grounds generations in Google Search and, new in this generation, Google Image Search. Thinking mode is on by default at a medium level and cannot be switched off. Every output carries a SynthID watermark. It generates at 1K, 2K and 4K; the 512px tier that Nano Banana 2 supported was dropped.

Gemini Omni Flash generates and edits video. Its documented pitch is "fast video generation, editing, keyframe interpolation, and extension with native audio," and the pricing page states it is "now generally available to developers on the paid tier of the Gemini API." Inputs are text, image, video and audio — audio being the modality Nano Banana 2.1 does not take. Generated clips carry synchronized dialogue and sound rather than arriving as silent assets. The Google video documentation is unusually directive about which video model to reach for: use Gemini Omni Flash as the default for video generation, and use Veo 3.1 for specific capabilities such as scene extension and higher-fidelity one-shot work.

• Output artefact — Gemini Nano Banana 2.1 produces still images and text; Gemini Omni 1.1 Flash produces video with synchronized native audio.

• Billing unit — Nano Banana 2.1 is billed per output image token; Omni 1.1 Flash is billed per output video token, with a published conversion of 5,792 output tokens per second of 720p.

• Headline price — Nano Banana 2.1 $0.0336 per 1K image at standard rates; Omni 1.1 Flash roughly $0.10 per second of 720p video.

• Input price — both $1.50 per million input tokens, but only Omni 1.1 Flash counts audio among the inputs.

• Text output — Nano Banana 2.1 $7.50 per million tokens; Omni 1.1 Flash $9.00 per million tokens for text, $17.50 for video.

• Provenance — Nano Banana 2.1 carries SynthID watermarking on every image; Omni 1.1 Flash's clip-level provenance is not stated on the pricing page.

• Independent measurement — neither model has a public arena placement in the days after its release; the only performance language for either is Google's own.

What the per-unit prices actually buy

Comparing $0.0336 with $0.10 is meaningless until you decide what a unit of output is. The honest version is a scene: a 30-second product clip at 720p is roughly $3.00 of Omni 1.1 Flash at the vendor's own conversion, and the still images that scene is built from are a fraction of a cent each on Nano Banana 2.1. A workflow that storyboards twelve frames, rejects ten of them and renders one final composition spends more on the eleven rejected stills than most people assume and less than the video by two orders of magnitude. That asymmetry is the entire reason the two models are usually chained rather than compared.

The pricing page also publishes a conversion that is easy to miss and important to know: 5,792 output tokens per second of 720p. That figure is what turns a token meter into a per-second budget, and it is the number to put into a cost model rather than the $0.10 headline, because the headline is derived from it under standard pricing. Google has not published an equivalent per-second figure for other resolutions on this model — its per-resolution rates belong to Veo 3.1, not to Omni Flash — so anyone quoting a 1080p or 4K per-second rate for Omni is quoting an estimate, not the page.

On the still side, Nano Banana 2.1's cost is unusually easy to reason about because both ends are published: $30 per million image tokens standard and $15 per million batch, with the token counts per resolution given (1,120 tokens for a 1K image, 1,680 for 2K, 2,520 for 4K). Batch at 1K is $0.0168 per image. If your pipeline can tolerate a 24-hour turnaround, the batch tier changes what a large reference-render pass costs.

The migration date that decides part of this

One half of this comparison is under a deadline and the other is not. On the same day Nano Banana 2.1 went GA, Google's changelog announced that gemini-3.1-flash-image — the model sold as Nano Banana 2 — "is deprecated and will be shut down on October 29, 2026." Gemini Omni Flash carries no such notice. So if you are currently running an image-plus-video pipeline on the previous image model, the still half of it is the half that needs attention in the next three weeks, and the video half is not.

That asymmetry is also why a two-model pipeline is worth wiring through one place. OrcaRouter fronts 200+ models behind a single OpenAI-compatible endpoint with 0% markup on provider list price and automatic failover between providers, so an image call and a video call come out of the same key, the same bill and the same retry logic instead of two vendor contracts with two failure modes. Neither of these two models is on our catalogue — Google's own API and several third-party platforms are where you get them — and the point is not that we host them; it is that when a model identifier changes under you, having it live in routing configuration rather than hard-coded in a deploy is what converts a deadline into a config edit. We do route other image models, including google/gemini-3.1-flash-image-preview and openai/gpt-image-2, which is what makes a live side-by-side against 2.1 possible without a second account.

Where the evidence stops

Neither model has an independent benchmark placement in the public record as of October 7, 2026. For Nano Banana 2.1 that is expected — it is a day old. For Omni 1.1 Flash it is a more interesting gap, because the model has been available longer and video generation is exactly the kind of task where human preference voting produces clear signal. Anyone who tells you one of these beats the other on measured quality is repeating a vendor claim or a hand-picked render. Google's stated improvements for Nano Banana 2.1 are in "visual quality, text rendering, multi-turn consistency, and Google Search grounding"; Google's stated framing for Omni 1.1 Flash is coherence and multi-input reasoning, with Veo 3.1 kept for extension and fidelity. Both are the vendor describing its own work.

The one thing you can verify without trusting anyone is behavioural. Omni 1.1 Flash is a video model: ask it for a still image and the request fails, because image generation and editing are not among the capabilities it lists. That is a routing question, not a quality question, and it is the failure mode that catches teams building a "one model does all my media" abstraction.

Which one your project needs

If the deliverable is a still — a product shot, a localized banner, an infographic with legible text, a character held consistent across a campaign — Gemini Nano Banana 2.1 is the model, and its four-character and ten-object consistency ceilings are the constraints to design around. If the deliverable moves and needs to sound like something, Gemini Omni 1.1 Flash is the model, and its per-second budget at 720p is the number to plan against. If both, the natural shape is the one Google's own docs imply: originate frames on the image model, animate the winner on the video model, and accept that you are buying two different units from two different meters.

The decision gets easier once you stop treating it as a head-to-head. There is no scenario in which paying $0.10 a second for 720p video is the wrong way to get a still, because it is not a way to get a still at all. The real comparison is between each of these and its own competitors — for Nano Banana 2.1 that means the cheap end of the image market rather than Nano Banana Pro, and for Omni 1.1 Flash it means Veo 3.1 on capability and whatever video model your budget actually allows.

What would settle it

Two developments would turn this from an architectural note into a decided comparison. The first is an independent image-editing placement for Nano Banana 2.1 — with its predecessor sitting in the middle of the pack on human-voted boards, the question of whether the "significant improvements" claim shows up in votes is genuinely open. The second is a published per-second rate for Omni 1.1 Flash above 720p, because until then every 1080p or 4K video budget built on this model is running on a reseller estimate rather than a Google figure.