Google DeepMind

Nano Banana 2

Best Value

9.1

out of 10

Google DeepMind's latest image generation model, officially Gemini 3.1 Flash Image (launched Feb 26, 2026). Delivers near-Pro quality at 25–50% lower cost than its predecessor, with 4K native output, multi-character consistency for up to 5 characters, best-in-class text rendering across languages, and web-grounded generation via Google Search. Default image model across Gemini app, Google Search AI Mode, and Google Ads in 141 countries. API pricing is tiered by resolution: 512px at $0.045, 1K at $0.067, 2K at $0.101, 4K at $0.151. Free via Gemini app and Flow.

Price

$0.067/image

Max resolution

4K native (512px / 1K / 2K / 4K tiers)

API

Supported

Commercial safety

Standard risk profile

Try Nano Banana 2 Rankings

Strengths

+25–50% cheaper than Nano Banana Pro at equivalent resolutions
+4K native output with 10+ aspect ratio configs including 21:9, 16:9, 4:1, and 8:1
+Multi-character consistency: up to 5 characters, 14 objects in a single workflow
+Best-in-class text rendering with character-by-character validation across multiple languages
+Web-grounded generation: pulls real-time Google Search data for accurate subject renders
+Widest ecosystem: Gemini app, Google Search, AI Studio, Vertex AI, Google Ads, Firebase
+SynthID watermarking + C2PA provenance built in — used 20M+ times since Nov 2025
+Free access via Gemini app and Flow (zero credits required)

Weaknesses

-Slightly artificial quality vs Nano Banana Pro — Pro output is more dynamic and realistic
-No published technical paper or official parameter count from Google
-Privacy concerns: allegations (unverified) of Google Photos training data use
-SynthID watermark bypass demonstrated via diffusion re-rendering (GitHub PoC exists)

Best for

API-integrated content pipelinestext-in-image generationmulti-character sceneshigh-volume enterprise image productionmarketing and ad creative at scaleGoogle ecosystem workflows

Pricing details

Free images: 0

API price per image: $0.067.

Last updated February 2026.

Launched February 26, 2026, Nano Banana 2 (officially Gemini 3.1 Flash Image) is Google's production-scale image generator — near-Pro quality at 25–50% lower cost, deployed across the Gemini app, Google Search, and Google Ads in 141 countries the day it launched. It's not the most beautiful image model in the world. That's still Midjourney. But no other model comes close to its combination of quality, speed, pricing, text rendering, multi-character consistency, and ecosystem reach. For developers and enterprise teams building at scale, this is the one.

The Nano Banana Family

Three models, two years, one of the most viral AI product franchises ever built.

Brand name	Technical name	Launch	Position
Nano Banana	Gemini 2.5 Flash Image	Aug 26, 2025	Original — launched anonymously on LMArena, #1 image editing model in days
Nano Banana Pro	Gemini 3 Pro Image	Nov 20, 2025	Studio-quality 4K — premium tier, still available for AI Pro/Ultra subscribers
Nano Banana 2	Gemini 3.1 Flash Image	Feb 26, 2026	Flash-speed + near-Pro quality — now the default across all Google surfaces

The original Nano Banana attracted 13 million first-time Gemini users in four days and drove 200+ million image edits within weeks of launch. Nano Banana 2 replaces it as the default — Pro remains available via model picker for Google AI Pro ($19.99/mo) and Ultra ($249.99/mo) subscribers.

Sources:Google: How Nano Banana got its name Google: Nano Banana 2 announcement

API Pricing — Tiered by Resolution

This is the biggest practical improvement over Nano Banana Pro: same quality range, lower API cost at every tier.

Resolution	Nano Banana 2	Nano Banana Pro	Savings
512px (new tier)	$0.045/image	N/A	—
1K	$0.067/image	$0.134/image	~50% cheaper
2K	$0.101/image	$0.134/image	~25% cheaper
4K	$0.151/image	$0.240/image	~37% cheaper

At 1K resolution (the most common API tier), Nano Banana 2 is exactly half the cost of Pro. The new 512px efficiency tier at $0.045 makes high-volume pipelines — ad creative generation, social thumbnails, product image variants — materially cheaper to run.

Sources:The Decoder: Nano Banana 2 pricing

What Nano Banana 2 Can Do

→

Multi-character consistencyMaintains subject resemblance for up to 5 characters and fidelity of up to 14 objects in a single generation workflow — solving one of the hardest long-standing limitations of diffusion models.

→

Text renderingCharacter-by-character validation for accurate, legible text in images across multiple languages. Includes in-image translation and localization — generate marketing copy in one language and render it accurately in another.

→

Web-grounded generationPulls real-time information and images from Google Search to render specific, recognizable subjects accurately — logos, landmarks, product packaging, public figures. No other image model has this capability at scale.

→

Thinking levels (API)Three configurable thinking levels: Minimal (fastest), High (better quality), and Dynamic (model decides based on prompt complexity). Controls quality-cost tradeoff per request.

→

Aspect ratio flexibilityOver 10 configurations including 21:9, 16:9, 4:3, 1:1, 3:4, 9:16, and new ultra-wide 4:1, 1:4, 8:1, 1:8 formats. Covers every production use case from billboard to mobile story.

→

Image editingNatural language prompt-based editing of existing images — same model, no separate editing API needed.

Speed & Quality — Independent Testing

Third-party benchmarks from Skywork.ai on RTX 4090 at 512×512 (FP16).

Metric	Nano Banana 2	Context
p50 latency (512px)	0.86 seconds	8–34% faster than comparable speed-tier models
Throughput	355 images/minute	16 parallel jobs
GPU utilization	94–97%	Efficient — minimal idle cycles
VRAM (16 parallel jobs)	~18.6 GB	Fits H100 / A100 40GB with headroom
CLIPScore (text-image alignment)	0.319 ± 0.006	Ahead of SD-Turbo (0.312), behind mid-weight quality models (0.341)

CLIPScore measures how well the generated image matches the text prompt. Nano Banana 2 beats speed-optimized competitors but trails dedicated quality-focused models. The tradeoff is intentional: this is a production-throughput model, not a gallery model.

Sources:Skywork.ai: Nano Banana 2 benchmark The Decoder: independent testing

Nano Banana 2 vs. the Competition

Where it wins, where it doesn't.

Competitor	Nano Banana 2 advantage	Where competitor wins
Nano Banana Pro	50% cheaper at 1K tier, same ecosystem	More dynamic and realistic output, worth it for hero images
FLUX.2	Structural clarity, identity recognition, text rendering, numerical reasoning	Cinematic mood, painterly aesthetics
Qwen-Image-2.0 (Alibaba)	Ecosystem integration, Google Search grounding, SynthID provenance	Potentially open-weight, very competitive raw quality
Midjourney v7	API access, pricing, text rendering, enterprise ecosystem	Pure aesthetic quality and artistic stylization
DALL-E / GPT ImageGen	Price, resolution range, multi-character consistency, Google ecosystem	OpenAI stack integration, Sora ecosystem

The Decoder's independent testing: Nano Banana 2 'holds its own against the Pro version' but 'the Pro output still looks more dynamic and realistic overall, while Nano Banana 2 has a slightly artificial quality to it.' For hero creative work, use Pro. For pipeline-scale production, Nano Banana 2 wins on cost.

Sources:The Decoder: Nano Banana 2 vs Pro VentureBeat: enterprise image generation analysis

Safety, Provenance & Controversies

Nano Banana's reach — 13 million new users in four days — has made it a flashpoint for deepfakes, privacy, and IP concerns.

Safety measures in Nano Banana 2

Feature	Detail
SynthID watermarking	Invisible cryptographic watermark embedded in generated pixels. Used 20M+ times since Nov 2025. Interoperable with C2PA Content Credentials standard.
C2PA Content Credentials	Cross-industry provenance framework backed by Adobe, Microsoft, Google, OpenAI, and Meta. Metadata persists through most (not all) image transformations.

Known limitation: a GitHub proof-of-concept (00quebec/Synthid-Bypass) demonstrated SynthID removal via diffusion model re-rendering. Reality Defender CEO Ben Colman: 'Watermarking at first sounds like a noble and promising solution, but its real-world applications fail from the onset when they can be easily faked, removed, or ignored.'

Sources:Forbes: Nano Banana privacy concerns

The privacy allegation — unverified

Proton (encrypted email company) posted: 'When you know the only reason Google's AI is the best at generating images because they're scanning every Android user's Google Photos albums but they won't admit it & you can't prove it.' Forbes noted the claim offered no evidence. Google has not confirmed or denied training on Google Photos data. An Indian user reported Gemini adding a mole matching one not visible in her uploaded photo — raising unresolved questions about data practices. These remain allegations, not proven facts.

Why it's called Nano Banana

At 2:30 AM before a submission deadline, Google DeepMind PM Naina Raisinghani needed a codename for an anonymous LMArena submission. She combined her two personal nicknames — 'Nano' (because she's short and likes computers) and 'Banana' (a friend's nickname for her). The placeholder became a global brand. The run button in AI Studio turned yellow. A banana emoji 🍌 appeared in the Gemini app. The team made banana swag. 'We've embraced the banana emoji as one of us.'

Bottom line

Nano Banana 2 is the best image generation model for production-scale API use. Midjourney v7 still wins on raw aesthetic quality for creative direction and hero images. Nano Banana Pro is still better for ultra-high-fidelity single-image work. But for developers building content pipelines, ad creative automation, or any use case that needs to generate thousands of images at reasonable cost — Nano Banana 2 is the answer. The text rendering, multi-character consistency, web grounding, and Google ecosystem integration are genuinely differentiated. The 50% price cut vs Pro is the business case on its own.