Google DeepMind's Nano Banana Pro (released November 20, 2025) and OpenAI's gpt-image-1.5 (current flagship) are the two image generation models worth comparing in 2026. They look similar on the surface — both render text cleanly, both accept multimodal input, both are priced per image. The differences show up exactly where production workflows care: native 4K, character consistency, and the cost curve.

This guide splits what each maker has officially documented from what third parties have reported, so the comparison stays honest.

TL;DR

Nano Banana Pro wins on native resolution (up to 4096×4096), explicit multi-character consistency (up to 5 people), and multi-image blending (up to 14 objects). Per-image pricing ~$0.13 at 1K/2K, ~$0.24 at 4K.
gpt-image-1.5 wins on draft cost ($0.009 per 1024×1024 Low), three-tier quality control, and already being the default inside ChatGPT. High quality runs $0.133–$0.200 per image.
Neither model is cheaper across the board. Cost-per-pixel flips depending on whether you need native 4K.
Both retire DALL·E — OpenAI officially sunsets DALL·E 2 and 3 on May 12, 2026.

Head-to-head at a glance

Criterion	Nano Banana Pro	GPT Image (gpt-image-1.5)
Maker	Google DeepMind	OpenAI
Model ID	`gemini-3-pro-image-preview`	`gpt-image-1.5`
Native 4K	Yes — up to 4096×4096	No — max 1024×1536 / 1536×1024
Character consistency (stated)	Up to 5	Not publicly specified
Multi-image blend	Up to 14 object inputs	Not publicly specified
Per-image pricing	~$0.13 at 1K/2K, ~$0.24 at 4K	$0.009–$0.200 by quality and size
Release	November 20, 2025	Current flagship — replaces DALL·E 3

Sources: Google DeepMind's Gemini 3 Pro Image (Nano Banana Pro) page and OpenAI's gpt-image-1.5 model spec.

Resolution: where Nano Banana Pro pulls ahead

Google DeepMind states plainly that Nano Banana Pro can "generate crisp visuals at 1k, 2k or 4k resolution." gpt-image-1.5 stops at 1024×1536 portrait or 1536×1024 landscape. For billboard work, product visualization at high DPI, or deliverables that need native 4K without upscaling artifacts, Nano Banana Pro is the only one of the two that gets you there in a single pass.

If your final output lives on an OLED display or in a print workflow that cares about native pixel density, the math is simple: you can either pay ~$0.24 per 4K Nano Banana Pro render, or generate at gpt-image-1.5 High and run the output through an upscaler. The upscaler adds latency and occasionally introduces its own artifacts, so for true 4K pipelines Nano Banana Pro's single-pass approach usually wins.

Pricing: gpt-image-1.5 wins drafts, Nano Banana Pro wins 4K

For Low-quality 1024×1024 drafts, gpt-image-1.5 is $0.009 per image — roughly 14× cheaper than Nano Banana Pro's 1K tier. That gap compounds in iterative workflows where you generate dozens of variations before picking a winner.

Move up the quality ladder and the gap closes:

Job	gpt-image-1.5	Nano Banana Pro
1024×1024 draft	$0.009 (Low)	~$0.13 (1K)
1024×1024 final	$0.133 (High)	~$0.13 (1K)
1536×1024 final	$0.200 (High)	~$0.13 (2K)
4K deliverable	Not supported	~$0.24 (4K)

Break-even is roughly at the 2K tier. Below it, gpt-image-1.5 is cheaper; above it, Nano Banana Pro is the only native option.

Source: OpenAI pricing from developers.openai.com/api/docs/models/gpt-image-1.5; Nano Banana Pro figures compiled from multiple third-party API aggregators (OpenRouter, pricepertoken.com). Google DeepMind's own product page does not publish a numeric per-image figure.

Character consistency and multi-image blending

Nano Banana Pro's explicit capability statement is the clearest signal in the category: "the consistency and resemblance of up to five characters and the fidelity of up to fourteen objects in a single workflow." That is the kind of phrasing that ends up on campaign briefs — "keep these five people recognizable across 20 shots."

OpenAI has not published an equivalent figure for gpt-image-1.5. In practice, the model maintains identity across edits to the same base image well, but cross-generation identity lock (same character, different scenes) is not a benchmark OpenAI promotes. If your brief requires identity continuity across a series, Nano Banana Pro has the explicit spec.

Text rendering inside images

Both models render in-image text at a much higher bar than DALL·E 3 ever did — that is, after all, why OpenAI is retiring DALL·E. Nano Banana Pro markets "clear text for posters and intricate diagrams" with multilingual translation. gpt-image-1.5 is what ChatGPT itself uses for signs, UI mockups, and product packaging.

For pure text-heavy creative (lengthy quotes, dense infographic labels, multilingual poster runs), Nano Banana Pro has the stronger current reputation. For everyday marketing creative where text is one element among many, gpt-image-1.5 is effectively indistinguishable on the visible result and cheaper at the Low and Medium tiers.

Access and rate limits

gpt-image-1.5 API rate limits scale by spend tier: Tier 1 accounts get 100,000 TPM and 5 images per minute; Tier 5 gets 8,000,000 TPM and 250 IPM. OpenAI promotes accounts between tiers automatically as historical spend accrues. Inside ChatGPT, the limits are plan-based (Free, Go, Plus, Pro) — see our ChatGPT image limits breakdown.

Nano Banana Pro is available in the Gemini app, Google AI Studio, and the Gemini API. Free-tier Gemini app users are capped at around three generations per day at lower resolution. Paid Gemini tiers and direct API usage raise the ceiling significantly. Google has not published a single public rate-limit table for the API tier equivalent of OpenAI's IPM scale; quotas are allocated per project at the Google Cloud console level.

Who should pick which

Choose Nano Banana Pro if	Choose gpt-image-1.5 if
You need native 4K output	You need cheap draft iteration ($0.009/image)
Multi-character consistency is on the brief	You want three quality tiers to manage spend
Your asset has heavy multilingual text	You already work in ChatGPT or the OpenAI stack
You already run on Google Cloud	You want three native sizes without upscaling

Choose both for real workflows. Draft at gpt-image-1.5 Low for speed and cost, finalize at Nano Banana Pro 4K when pixel density matters. The two models are complements more than competitors at different points in the pipeline.

Frequently asked questions

What is the difference between Nano Banana Pro and GPT Image?

Nano Banana Pro is Google DeepMind's image model built on Gemini 3 (model id gemini-3-pro-image-preview), released November 20, 2025. GPT Image (current model id gpt-image-1.5) is OpenAI's flagship image model. The two main differences: Nano Banana Pro renders native 4K (up to 4096×4096) while gpt-image-1.5 tops out at 1536×1024; Nano Banana Pro is priced per image at roughly $0.13 (1K/2K) or $0.24 (4K) while gpt-image-1.5 charges per image by quality tier from $0.009 to $0.200.

Is Nano Banana Pro actually 4K?

Yes. Google DeepMind states the model can "generate crisp visuals at 1k, 2k or 4k resolution" (source). Native 4K means 4096×4096 pixels without upscaling. gpt-image-1.5 does not offer a 4K tier — its maximum native output size is 1024×1536 or 1536×1024.

Does gpt-image-1.5 support character consistency?

OpenAI has not published a dedicated "character consistency" figure for gpt-image-1.5 in the way Google has for Nano Banana Pro (up to 5 characters). In practice, gpt-image-1.5 maintains identity across edits on the same base image well; across completely new generations, Nano Banana Pro currently has the explicit capability statement.

Which one is cheaper?

For drafts, gpt-image-1.5 at Low quality ($0.009 per 1024×1024 image) is the cheapest option on the market. For high-fidelity 2K or 4K output, Nano Banana Pro (~$0.13 at 1K/2K, ~$0.24 at 4K) is usually a lower cost-per-pixel than upscaling gpt-image-1.5 High output. Break-even depends on whether you need native 4K.

Can I use both models from one platform?

Yes. The studio on gptimg.co wraps multiple GPT Image model variants and can route prompts to Google Nano Banana models as well. You switch models from the dropdown without setting up separate API keys for OpenAI and Google. Credit packs are shared across models, with per-render cost reflecting the underlying model price.

Where can I try each one free?

Nano Banana Pro is available inside the Gemini app and Google AI Studio with a free quota. gpt-image-1.5 runs inside ChatGPT (Free and paid plans) and inside the studio at gptimg.co/gpt-image-1-5 with a daily free quota. For production work, both are available via OpenAI's and Google's respective APIs at the per-image prices above.

Try gpt-image-1.5 free

The fastest way to evaluate gpt-image-1.5 against your own brief is to run a few prompts through it. The gpt-image-1.5 studio runs the model directly in your browser — free trial credits on signup, no OpenAI API key required, no install.

For Nano Banana Pro, head to Google AI Studio or the Gemini app.

Sources

Gemini 3 Pro Image (Nano Banana Pro) — Google DeepMind product page
gpt-image-1.5 model spec — OpenAI developers documentation
OpenAI API Deprecations — DALL·E 2 and 3 retirement notice (May 12, 2026)

Last reviewed against source pages: 2026-04-17. Pricing and capability figures change periodically; confirm in the linked sources before acting on the numbers above.