Nano Banana Pro 1M input/output tokens price and performance

Complete Analysis: 2,000,000 tokens for Nano Banana Pro

Complete analysis of pricing, performance, and use cases for Google's Nano Banana Pro model .

$0.134000 (rounded ~ $0.13) Total Cost
2,000,000 Total Tokens
27 minutes, 46.85 seconds Processing Time

Click Recalculate to update after making changes

Select AI Model

Nano Banana Pro
GoogleMax Context: 4,096 tokens
$0.134 (std) / $0.24 (HD) / $0.48 (4K) per image
Use Batch API (50% discount)
0%
Provider-specific multipliers applied after all calculations
Enable for cache discounts
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.
Will auto-convert to minutes for Voxtral models (9000 tokens = 1 min)
$0.067 per 1,000 pixels

Calculate Token Costs

$0.000000 Input Cost
$0.000000 Output Cost
$0.134000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
2,000,000Total Tokens
$0.000067Cost per 1K
14,925,373Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

27m 46s Processing Time
1,200 Tokens/Second
50ms Time to First Token
1,200 Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 Advanced Options

⚡ Optimization
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data
First 50 hours free, $0.05/hour after

🧠 Reasoning & Thinking
Manual thinking tokens (billed at output rate)

🔧 Special Modes
Enable 6.0x Fast Mode multiplier

📚 Research & Citations
Enable $1.00/$4.00 rates + $10.00/1k search
Enable research tier pricing
Fee per source cited

🎤 Realtime Audio & Video
Session length for billing

Nano Banana Pro Google

$0.134000 (rounded ~ $0.13)
Total Cost
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
Caching
✗ Not Available

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.134000 (rounded ~ $0.13) Input: $0.000000
Output: $0.000000
Optimized Cost $0.134000 (rounded ~ $0.13) Input: $0.000000
Output: $0.000000
Unit: $0.134000 (rounded ~ $0.13)
Fees: $0.000000

Advanced Cost Breakdown (from Plugin)

Detailed Cost Analysis (from Plugin)

For 1,000,000 input tokens and 1,000,000 output tokens:

  • Input Cost: $0.000000
  • Output Cost: $0.000000
  • Unit Cost: $0.134000 (rounded ~ $0.13)
  • Total Cost: $0.134000 (rounded ~ $0.13)
  • Cost per 1K tokens: $0.000067
  • Tokens per dollar: 14,925,373 tokens
  • Context Window: 4096 tokens
  • Thinking Source: (0 tokens)

Speed & Performance Analysis

With a processing speed of 1,200 tokens per second and 50ms time to first token:

  • Processing Time: 27 minutes, 46.85 seconds
  • Latency: 50 milliseconds to first token
  • Base Throughput: 1,200 tokens/second

Best Use Cases

Edge ComputingLocal Privacy Reasoning

Want this applied to YOUR actual stack?

This calculator shows the math for Nano Banana Pro. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

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✨ Market Recommendations AI Model Registry

← Back to Nano Banana Pro
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000,000
Rank AI Model & Provider Total Cost vs Nano Banana Pro
🏆 Llama 4 Scout
Meta AI
$0.380000 Best Value ↑ 183.6% more
🥈 Grok 4.20 Beta
xAI
$8.000000 ↑ 5870.1% more
🥉 Gemini 2.5 Pro
Google
$17.500000 ↑ 12959.7% more
#4 Gemini 2.5 Pro
Google
$17.500000 ↑ 12959.7% more
🏆

Llama 4 Scout
Meta AI

$0.380000
vs Nano Banana Pro: ↑ 183.6%
🥈

Grok 4.20 Beta
xAI

$8.000000
vs Nano Banana Pro: ↑ 5870.1%
🥉

Gemini 2.5 Pro
Google

$17.500000
vs Nano Banana Pro: ↑ 12959.7%
#4

Gemini 2.5 Pro
Google

$17.500000
vs Nano Banana Pro: ↑ 12959.7%
✨ How recommendations work (v8.6.0): We scan all active models in the registry and only include those that support ALL your current inputs. For token-based models, we check if they can handle your token counts. For special pricing models (OCR, video, audio), we verify they have the correct pricing structure. Features marked requested were in your inputs but not supported by that model. Now using official provider pricing without reseller markups.

Next-Generation Nano Banana Pro Intelligence

Nano Banana Pro is a frontier model from Google optimized for the 2026 AI landscape.

Frequently Asked Questions

How accurate are these AI model cost calculations?
Our calculations are based on official pricing from each provider (Google, OpenAI, Anthropic, Meta, xAI, Perplexity, DeepSeek, Mistral) and are updated regularly. We account for all factors including multimodal inputs, caching discounts, batch API pricing, tool usage multipliers, OCR processing, audio minutes, silence fees, and research mode pricing. Note: Reseller markups and dedicated instance multipliers have been removed to reflect official provider pricing.
How do Market Recommendations work (v8.6.0)?
Our recommendation engine scans the entire model registry and only includes models that support ALL your current input parameters (tokens, images, video, audio, OCR, tools, batch API, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options that can handle your complete workflow. Special pricing models (OCR, video, audio, image generation) are properly handled and only appear when their specific input types are requested. v8.6.0 removes reseller markups (20% buffer) and dedicated instance multipliers to reflect official provider pricing.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 50+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), provides optimization recommendations, and now offers intelligent market matching to find the best alternatives for your specific needs.