Model profile
google

Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview)

Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview) is a budget multimodal generalist from google with a heavy runtime profile, standard context posture, and the clearest fit around multimodal / long-context research.

Best for: Multimodal / Long-context researchHeavy latencyStandard contextBudget pricing
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
66K Tokens

Standard

Input Price
$0.50

Budget tier

Decision snapshot
54

Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview) currently reads as a budget multimodal option with standard context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Multimodal / Long-context research
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouterVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
N/A
44

General reasoning and benchmark headroom.

Situational
Speed
N/A
46

Latency data is partial.

Situational
Context
66K Tokens
64

How much prompt and task state can stay in view.

Competitive
Price
$0.50
86

$3.00 output / 1M

Efficient

Editorial Profile

Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 40Math score 36Vision enabled

Gemini 3.1 Flash Image Preview, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced contextual understanding with fast, cost-efficient inference, making complex image generation and iterative edits significantly more accessible. Aspect ratios can be controlled with the [image_config API Parameter](https://openrouter.ai/docs/features/multimodal/image-generation#image-aspect-ratio-configuration)

Identity

google multimodal profile

Positioning

Multimodal / Long-context research with standard context and heavy runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Context window is more comfortable for focused tasks than extremely long sessions.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

No benchmark data is available for this model yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
66K Tokens
Vision
Enabled
Modalities
text, image->text, image
Tokenizer
Gemini
Max Completion
65536
Moderation
No
Supported Parameters
include_reasoningmax_tokensreasoningresponse_formatseedstopstructured_outputstemperaturetop_p
Input Modalities
imagetext
Output Modalities
imagetext
Price architecture
Input
per 1M input tokens
$0.50
Output
per 1M output tokens
$3.00
Blended
AA 3:1 mix
N/A

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.