Googleactive

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

Released at: June 30, 2026

API StatusAvailable for integration
Context Window65,536 tokens✓ verified today
Input Price / MTok$0.25✓ verified today
Output Price / MTok$1.50✓ verified today

Model Overview

Google · Active Model

  • API Available
  • Vetted Benchmarks
  • Production Ready

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) by Google — Technical Architecture, Empirical Benchmarks & API Specs§

1. Executive Summary & Core Positioning§

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is an advanced artificial intelligence model engineered by Google. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) represents a key architectural iteration in the Google model family. First released in 2026-06-30, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 65,536 tokens (approximately 87 words), Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) based on verified provider metadata:

  • Model Name: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)
  • Developer / Provider: Google
  • Context Window Capacity: 65,536 tokens (~87 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "nano-banana-2-lite-gemini-3-1-flash-lite-image",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 65,536 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image):

  • Input Token Cost: $0.25 per MTok
  • Output Token Cost: $1.50 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)**Provider Ecosystem Baseline
DeveloperGoogleIndustry Average
Context Window65,536 tokens128,000 tokens
Input Price / MTok$0.25Variable
Output Price / MTok$1.50Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)'s context window limit?§

A: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) supports an input context window of 65,536 tokens.

Q: What is the API pricing for Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)?§

A: Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is priced at $0.25 per million input tokens and $1.50 per million output tokens.

Q: Is Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) accessible via API?§

A: Yes, Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is available for programmatic integration.

Developer
Google✓ verified today
Release Date
June 30, 2026✓ verified today
Context Window
65,536 tokens87 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$0.25per million tokens✓ verified today
Output Cost
$1.50per million tokens✓ verified today
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Vetted Benchmarks

MMLU(estimated)Score: 75.0% (Top 85%)
HumanEval(estimated)Score: 71.2% (Top 86%)
MATH(estimated)Score: 44.4% (Top 81%)
MT-Bench(estimated)Score: 8.2 (Top 79%)
GPQA(estimated)Score: 28.4% (Top 100%)
HellaSwag(estimated)Score: 75.6% (Top 99%)

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Originally published on llmdb.app

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