Ideogram V4 vs Nano Banana 2: Open-Weight Typography vs Closed Gemini Image

Ideogram V4 is the stronger pick for typography-heavy design work, winning a blind ten-designer study 47.9% to 30.0% against Nano Banana 2 — Google's Gemini 3.1 Flash Image Preview — while Nano Banana 2 remains a closed model inside the broader Gemini stack; the right choice depends on whether you need open weights and precise text rendering or Google's general-purpose image reasoning.

Key Takeaways

• Ideogram V4 is an open-weight 9.3B-parameter single-stream Diffusion Transformer from Ideogram AI, released June 3, 2026, with a Qwen3-VL-8B text encoder and native 2048-pixel output.
• Nano Banana 2 is the community name for Google's Gemini 3.1 Flash Image Preview, a closed image generation model in the Gemini family; internal architecture and parameter count are not publicly disclosed.
• On the ContraLabs blind typography evaluation, Ideogram V4 was picked first 47.9% of the time versus 30.0% for Nano Banana 2, per the Ideogram 4 model card.
• On the same designer study, Ideogram V4 scored 3.55/5 for "would you use this in real client work" versus 2.84/5 for Nano Banana 2.
• Ideogram V4 has published per-image API pricing ($0.03 Turbo, $0.06 Default, $0.10 Quality); Nano Banana 2 pricing details are not confirmed in public sources reviewed here.
• Ideogram V4 ships NF4 and FP8 weights on Hugging Face under a non-commercial license; Nano Banana 2 has no public weights.

Ideogram V4 vs Nano Banana 2 at a Glance

Dimension	Ideogram V4	Nano Banana 2
Vendor	Ideogram AI	Google (Gemini family)
Model family	Standalone image foundation model	Gemini 3.1 Flash Image Preview
Architecture	9.3B single-stream Diffusion Transformer, Qwen3-VL-8B text encoder	Not publicly disclosed
Open weights	Yes — NF4 and FP8 on Hugging Face	No
License	Apache 2.0 code; Ideogram 4 Non-Commercial weights	Closed, Google terms
Native resolution	Up to 2048×2048	Not yet confirmed in public sources here
API price (per image)	$0.03 Turbo / $0.06 Default / $0.10 Quality	Not yet confirmed
Text rendering (X-Omni English OCR)	0.97	Not yet confirmed
Designer first-pick rate (ContraLabs)	47.9%	30.0%
Designer "real client work" score	3.55 / 5	2.84 / 5
Structured prompting	JSON prompt schema with bounding boxes and hex palettes	Natural language via Gemini API

Capabilities

Ideogram V4 accepts either a plain text_prompt or a structured json_prompt that carries bounding-box coordinates and hex color palettes, letting a caller pin regional content and layout deterministically. Its /v1/ideogram-v4/generate endpoint returns hosted image URLs; sibling endpoints cover remix, describe (which returns a reusable structured V4 JSON prompt), and asynchronous webhook generation, per the Ideogram developer documentation. Native 2048-pixel output and built-in typography handling are what most V4 workflow guides highlight when they call it "design-forward."

Nano Banana 2 sits inside the Gemini stack as Gemini 3.1 Flash Image Preview, so its capability surface follows Google's Gemini image API conventions rather than a bespoke design schema. Public benchmark writeups treat it as a general-purpose image generator paired with Gemini's language reasoning; a dedicated structured layout schema comparable to Ideogram's json_prompt has not been documented in the sources reviewed here.

For teams that want the closest hosted alternative for text-to-image generation with a similar design focus, the Ideogram V3 API endpoint stays available on kie.ai alongside its editing tools. Our earlier deep-dive on the model architecture — Ideogram V4 Is a 9.3B Diffusion Transformer With Open Weights and $0.03 Turbo Image Generation — covers the internals in more detail.

Benchmarks

Ideogram V4's benchmark story is unusually well-documented for an image model. On the X-Omni English OCR benchmark for in-image text accuracy, it scores 0.97, and on the 7Bench layout benchmark it reports 0.69 mIoU, per the Ideogram 4 model card on Hugging Face. On Arena.ai's text-to-image leaderboard it holds the #1 open-weight position at ELO 1204, and on Design Arena it leads the next open-weight model by roughly 115 ELO.

The most direct head-to-head data point with Nano Banana 2 comes from ContraLabs, a third-party blind typography evaluation judged by ten professional designers. Per the Ideogram model card, Ideogram V4 was picked first 47.9% of the time, versus 30.0% for Nano Banana 2 (Gemini 3.1 Flash Image Preview), 15.5% for FLUX.2 [max], and 15.0% for Grok Imagine 1.0. On the practical question "Would you use this in real client work?", the same designers scored Ideogram V4 at 3.55/5 against Nano Banana 2's 2.84/5.

That is a real typography lead, but the scope is narrow: one blind study, one design task family, ten judges. Nano Banana 2 does not yet have comparable public numbers on general prompt-adherence, world knowledge, or photorealism against Ideogram V4 in the material available here — the head-to-head data outside typography is still thin.

Pricing

Ideogram V4's official API is priced per image: $0.03 for the Turbo tier, $0.06 for Default, and $0.10 for Quality, according to Ideogram's API pricing page. Subscription plans on ideogram.ai run $7 to $42 per month on annual billing and cover commercial use of outputs, per Ideogram's FAQ.

Nano Banana 2's per-image or per-token image pricing has not been confirmed in the public sources reviewed here. It is billed through Google's Gemini API surface, so any comparison against Ideogram V4's per-image ladder should be treated as unverified until Google publishes explicit Gemini 3.1 Flash Image Preview rates.

Availability and Licensing

Ideogram V4's inference code is Apache 2.0. The weights are published on Hugging Face in NF4 (ideogram-ai/ideogram-4-nf4) and FP8 variants under the Ideogram 4 Non-Commercial license, and community-run integrations in ComfyUI, Draw Things, and other local tools are already live. fal has separately open-sourced distilled Instant and Fast variants that push single-image generation into the sub-second range, per fal's Hugging Face release.

Nano Banana 2 has no public weights, no local inference path, and no third-party quantizations. Access runs through Google's Gemini API and Gemini-powered surfaces only. That is the defining split: Ideogram V4 has an open, self-hostable footprint (subject to its non-commercial weight license) while Nano Banana 2 is a fully managed Google service.

The commercial-use asymmetry matters for shipping teams. A Reddit thread on r/StableDiffusion captures the concern: creators using local Ideogram V4 weights to generate imagery for a book or comic have to route through the paid API or subscription to clear commercial rights on those outputs, since the open weights carry a non-commercial license. Nano Banana 2's usage terms flow from Google's standard Gemini API contract instead.

Which One Should You Use?

Choose Ideogram V4 if:

• Typography, poster layout, or packaging text needs to be legibly and accurately rendered on the first try.
• You want structured json_prompt control with bounding boxes and hex palettes for reproducible layouts.
• Open weights and local inference (or the fal Instant/Fast distilled variants) matter for your stack.

Choose Nano Banana 2 if:

• You are already building on Google's Gemini API and want image generation inside that same surface.
• You need a closed, managed service with Google's Gemini-family language reasoning attached.
• Broad general-purpose image generation matters more to you than fine-grained typography control.

Frequently Asked Questions

Is Ideogram V4 better than Nano Banana 2?

Ideogram V4 outperforms Nano Banana 2 on typography and layout control, winning 47.9% of first-place picks in a blind ten-designer typography study versus 30.0% for Nano Banana 2. Nano Banana 2 has broader general-purpose image reasoning as part of Google's Gemini stack.

Is Ideogram V4 cheaper than Nano Banana 2?

Ideogram V4's official API starts at $0.03 per image on the Turbo tier and reaches $0.10 on Quality. Nano Banana 2's public per-image pricing is not confirmed in official Gemini image documentation that is available here, so a direct like-for-like price comparison is not yet possible.

Can I run Ideogram V4 locally? Can I run Nano Banana 2 locally?

Ideogram V4 ships public NF4 and FP8 weights on Hugging Face under a non-commercial license and can run locally on a 24GB-class GPU. Nano Banana 2 is a closed Google model with no public weights and cannot be run locally.

Which model has better text rendering, Ideogram V4 or Nano Banana 2?

Ideogram V4 has better text rendering. It scores 0.97 on the X-Omni English OCR benchmark and won a blind typography study by professional designers with a 47.9% first-place rate against Nano Banana 2's 30.0%.

Is Nano Banana 2 the same as Gemini 3.1 Flash Image?

Yes. Nano Banana 2 is the community and product name for Gemini 3.1 Flash Image Preview, Google's image generation model in the Gemini family, according to a third-party designer benchmark cited on the Ideogram V4 model card.

Which model should I use for posters and marketing design?

Ideogram V4 is the stronger pick for posters, packaging, and marketing design when readable typography is a hard requirement. It ranks first among open-weight models on Design Arena and leads Nano Banana 2 on designer usability scores.

Do Ideogram V4 outputs come with commercial rights?

Ideogram V4's paid API and subscription outputs are cleared for commercial use, per Ideogram's FAQ. The open weights on Hugging Face are released under the Ideogram 4 Non-Commercial license, so local generations from those weights are not licensed for commercial use.

What to Watch Next

Three signals will move this comparison. First, whether Google publishes official Gemini 3.1 Flash Image Preview pricing and benchmark numbers — that is the single biggest gap in this page today. Second, whether ContraLabs or a comparable third party runs a broader head-to-head that goes beyond typography into general prompt-adherence and photorealism. Third, whether Ideogram loosens or clarifies the open-weight license, since the non-commercial restriction is the loudest complaint from community adopters.

Building similar text-to-image workflows? On kie.ai you can try Ideogram V3, Nano Banana 2, and Seedream 4.0.