Nano Banana Pro vs Nano Banana 2: Specs & Pricing Comparison (2026)

Google DeepMind shipped two image models in roughly three months: Nano Banana Pro on November 20, 2025 and Nano Banana 2 on February 26, 2026. Same family, same headline capabilities (4K, web grounding, multilingual text), very different price-per-image. This Nano Banana Pro vs Nano Banana 2 comparison is built strictly from Google's documentation and the official Gemini API pricing page. Every number traces to a source URL.

Pro is the high-fidelity tier with thinking mode and a $0.24 4K render. Nano Banana 2 is the Flash tier, same Pro-grade quality framing at half-or-less per-image cost, aimed at fast iteration.

TL;DR

• Nano Banana Pro (gemini-3-pro-image-preview), released November 20, 2025; 1K/2K at $0.134 per image, 4K at $0.24 per image; supports thinking mode, Google Search grounding, up to 5-character consistency, up to 14 image inputs.
• Nano Banana 2 (gemini-3.1-flash-image-preview), released February 26, 2026; $0.045 at 0.5K, $0.067 at 1K, $0.101 at 2K, $0.151 at 4K per image; same 5-character / 14-object framing, web grounding, "Pro-level visual quality at Flash speed."
• Both support 512px to 4K output, multilingual text rendering, SynthID watermarks, and 65,536-token context windows.
• Pick Pro for hero finals where thinking-mode reasoning and the highest text-rendering bar matter; pick 2 for iteration loops where you generate dozens of variations before locking the winner.

Side-by-side specs

Sources: Nano Banana Pro launch post, Nano Banana 2 launch post, Gemini 3 Pro Image — Google DeepMind, Developers can build with Nano Banana Pro, Gemini Developer API pricing, and OpenRouter listings for gemini-3-pro-image-preview and gemini-3.1-flash-image-preview.

Pricing: where the gap actually lives

Google's official Gemini Developer API pricing is the only authoritative source for per-image cost; third-party aggregators occasionally reorder the numbers. Here's what Google publishes on that page, side by side:

Two things to notice. Pro charges a flat $0.134 from 1K through 2K, while Nano Banana 2 prices climb with resolution. And the Pro vs 2 cost ratio narrows as resolution rises: Pro is exactly 2× at 1K but only 1.59× at 4K. If your deliverable is 4K, the price gap is smaller than the 1K headline suggests. Batch mode cuts both prices roughly in half.

Cost example calculations

Three realistic scenarios, all at standard (non-batch) pricing per Google's pricing page.

Scenario A, 100 social posts at 1K final. A small team running daily social creative.

• Nano Banana Pro: 100 × $0.134 = $13.40
• Nano Banana 2: 100 × $0.067 = $6.70
• Savings with 2: 50% / $6.70

Scenario B, iteration loop: 30 drafts at 1K, 5 finals at 4K.

• Pro pure: 30 × $0.134 + 5 × $0.24 = $5.22
• 2 pure: 30 × $0.067 + 5 × $0.151 = $2.77
• Hybrid (drafts on 2, finals on Pro): 30 × $0.067 + 5 × $0.24 = $3.21

The hybrid keeps Pro's thinking-mode reasoning for the keepers while making drafts cheap.

Scenario C, 200 4K hero renders for a campaign.

• Pro: 200 × $0.24 = $48.00
• 2: 200 × $0.151 = $30.20 (~37% savings)

At 4K hero scale Nano Banana 2 saves real money, but Pro is the tier Google markets for "professional production" deliverables. The trade is dollars vs. one of Pro's distinguishing capabilities.

Capabilities: what's identical and what isn't

Identical (or near-identical) on paper

• Max resolution. Both top out at 4096×4096. The Nano Banana 2 launch post lists "512px to 4K"; the Nano Banana Pro DeepMind page states "1k, 2k or 4k resolution."
• Character / object framing. Both posts use identical numerical framing: "up to five characters" and "up to 14 objects."
• Multilingual text, web grounding, SynthID watermark. All three are documented for both models.
• Context window. OpenRouter lists 65,536 tokens for both gemini-3-pro-image-preview and gemini-3.1-flash-image-preview.

Where Pro is documented to do more

• Thinking mode is explicit on Pro. Google's Pro launch post says you "select 'Create images' with the 'Thinking' model" in the Gemini app. The pricing page bills text/thinking output tokens for Pro at $12/1M. Nano Banana 2 has chain-of-thought capability but Google doesn't surface it as a user-facing toggle the same way.
• Camera control language is more detailed for Pro. The Pro DeepMind page calls out "wide angle, panoramic, close up" framing and "depth of field." The Nano Banana 2 post focuses on "vibrant lighting, richer textures and sharper details."
• Heavier reasoning budget per render. Pro's text/thinking output is priced 4× higher per million tokens than Flash, reflecting a larger reasoning allocation per image.

Where Nano Banana 2 has the edge

• A 0.5K (512px) tier Pro doesn't offer. At $0.045 per image, this is the cheapest official Gemini-family option for fast thumbnails or layout proofs.
• Roughly half the cost at every shared resolution tier. Documented above.
• "Flash speed" framing. Google positions Nano Banana 2 as delivering "Pro-level visual quality at Flash speed." It's the iteration tool of the pair.

Claimed vs. independently confirmed

Google's launch posts are the source for the capability claims above. The Pro DeepMind page is the only place Google publishes single-line text rendering benchmarks across languages, described as "lowest error rates (mostly under 10%)." Independent head-to-head benchmarks comparing Nano Banana Pro and Nano Banana 2 on text rendering, character consistency, or instruction following are not yet published in arXiv or in the major model leaderboards.

So: per-image prices and resolution tiers are confirmed by Google's pricing page. 5-character / 14-object framing is identical wording in both posts, a Google claim, not an independent test result. The "Pro-level quality at Flash speed" framing for Nano Banana 2 is Google's marketing language; apples-to-apples quality scores between the two models are not yet in the public record. If your brief depends on a specific quality difference, run both against your own prompts before committing.

When to pick which

For most production workflows, a hybrid pipeline works best: draft on Nano Banana 2 to keep iteration cheap, then lock the winner on Nano Banana Pro for the heavier reasoning budget on the final render. Scenario B above shows the hybrid landing roughly $2 cheaper than pure-Pro across 35 renders, with no loss on the final-quality tier.

The original Nano Banana (Gemini 2.5 Flash Image) remains in service as the cheapest entry point. See our overview for where it still fits.

Frequently asked questions

What's the difference between Nano Banana Pro and Nano Banana 2?

Nano Banana Pro is gemini-3-pro-image-preview, released November 20, 2025, built on Gemini 3 Pro, priced at $0.134 per 1K/2K image and $0.24 per 4K image. Nano Banana 2 is gemini-3.1-flash-image-preview, released February 26, 2026, built on Gemini 3.1 Flash, priced at $0.045 (0.5K) to $0.151 (4K) per image. Both offer up to 4096×4096 output, multilingual text rendering, web grounding, and the same 5-character / 14-object framing in Google's launch posts. The main differentiators are Pro's explicit thinking mode and roughly 2× higher per-image cost at 1K.

Is Nano Banana 2 actually cheaper than Nano Banana Pro?

Yes, at every shared resolution. Per Google's Gemini Developer API pricing page: 1K is $0.067 vs $0.134 (50% less), 2K is $0.101 vs $0.134 (~25% less), and 4K is $0.151 vs $0.24 (~37% less). The savings are largest at 1K and smallest at 4K. Batch mode applies a 50% discount to both models.

Does Nano Banana 2 support 4K output?

Yes. The Nano Banana 2 launch post specifies "512px to 4K" with full aspect ratio control. Per-image pricing for 4K is $0.151, currently the cheapest 4K tier in the Gemini image family.

Does Nano Banana Pro have a "thinking" mode that Nano Banana 2 doesn't?

Google's Pro launch post explicitly calls out a Thinking model toggle in the Gemini app under "Create images." The pricing page bills text/thinking output tokens separately for both models, so Nano Banana 2 has chain-of-thought capability, but Pro is the tier Google currently surfaces a user-selectable Thinking option for.

Which model has higher quality?

Google positions Nano Banana 2 as delivering "Pro-level visual quality at Flash speed," which implies parity. Independent head-to-head benchmarks comparing the two on text rendering accuracy, character consistency, and instruction following are not yet published in the public record. For brand-critical work, run both against your own prompts before committing.

Can I use both Nano Banana models from one tool?

Yes. The studio at gptimg.co wraps both Nano Banana Pro and Nano Banana 2 alongside other Gemini-family options. You can switch models from the dropdown without managing separate Google API keys; credit packs are shared across models with per-render cost reflecting Google's per-image price.

Where can I try each one free?

Both are available in Google AI Studio and the Gemini app. Free-tier quota is limited; for production workloads use the Gemini API or a wrapper that surfaces both models.

Try Nano Banana Pro and Nano Banana 2 free

The fastest way to compare the two against your own brief is to run a few prompts through each one. Open Nano Banana Pro on gptimg.co for the high-fidelity tier or Nano Banana 2 on gptimg.co for fast iteration. Both run directly in your browser with free trial credits on signup, no Google API key required.

If you're new to the family, start with our Nano Banana model overview for context on which tier fits which workload.

Sources

• Nano Banana Pro: Gemini 3 Pro Image model from Google DeepMind, Google launch blog, November 20, 2025
• Developers can build with Nano Banana Pro (Gemini 3 Pro Image), Google developer announcement
• Gemini 3 Pro Image — Google DeepMind, official product page
• Nano Banana 2: Google's latest AI image generation model, Google launch blog, February 26, 2026
• Gemini Developer API pricing, official per-image pricing page
• OpenRouter — gemini-3-pro-image-preview, third-party API listing with token pricing
• OpenRouter — gemini-3.1-flash-image-preview, third-party API listing with token pricing

Last reviewed against source pages: 2026-04-18. Pricing and capability figures are pulled directly from Google's documentation; confirm in the linked sources before acting on the numbers above.