Nano Banana Pro Google
💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $670.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 100 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $670.000000
- Total Cost: $670.000000
- Cost per 1K tokens: $1.339732
- Tokens per dollar: 746 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: 6 minutes, 56.93 seconds
- Latency: 50 milliseconds to first token
- Base Throughput: 1,200 tokens/second
Best Use Cases
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← Back to Nano Banana Pro| Rank | AI Model & Provider | Total Cost | vs Nano Banana Pro |
|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.290113 Best Value | ↓ 100% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.348153 (rounded ~ $0.35) | ↓ 99.9% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.348153 (rounded ~ $0.35) | ↓ 99.9% cheaper |
| #4 |
Gemini 3.8 Flash
Google
|
$0.870319 | ↓ 99.9% cheaper |
| #5 |
GPT-5.6 Luna
OpenAI
|
$1.160450 | ↓ 99.8% cheaper |
| #6 |
Gemini 3.6 Flash
Google
|
$1.740638 | ↓ 99.7% cheaper |
| #7 |
Gemini 3.5 Flash
Google
|
$1.740675 | ↓ 99.7% cheaper |
| #8 |
Claude Sonnet 5
Anthropic
|
$2.320850 | ↓ 99.7% cheaper |
| #9 |
Gemini 3.1 Flash
Google
|
$2.320900 | ↓ 99.7% cheaper |
| #10 |
GPT-5.6 Terra
OpenAI
|
$2.901125 (rounded ~ $2.90) | ↓ 99.6% cheaper |
| #11 |
Claude Sonnet 4.6
Anthropic
|
$3.481275 (rounded ~ $3.48) | ↓ 99.5% cheaper |
| #12 |
Claude Opus 4.7
Anthropic
|
$5.802125 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #13 |
Claude Opus 5
Anthropic
|
$5.802125 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #14 |
Claude Opus 4.8
Anthropic
|
$5.802125 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #15 |
Claude Opus 4.6
Anthropic
|
$5.802125 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #16 |
Gemini 2.5 Pro
Google
|
$5.802250 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #17 |
GPT-5.6 Sol
OpenAI
|
$5.802250 (rounded ~ $5.80) | ↓ 99.1% cheaper |
| #18 |
Grok 4.3
xAI
|
$9.282800 (rounded ~ $9.28) | ↓ 98.6% cheaper |
| #19 |
Gemini 3.1 Pro
Google
|
$9.283300 (rounded ~ $9.28) | ↓ 98.6% cheaper |
| #20 |
Claude Fable 5.1
Anthropic
|
$11.392000 (rounded ~ $11.39) | ↓ 98.3% cheaper |
| #21 |
Claude Mythos 5.1
Anthropic
|
$11.392000 (rounded ~ $11.39) | ↓ 98.3% cheaper |
| #22 |
GPT-5.4
OpenAI
|
$11.604125 (rounded ~ $11.60) | ↓ 98.3% cheaper |
| #23 |
GPT-5.4 Thinking
OpenAI
|
$11.604125 (rounded ~ $11.60) | ↓ 98.3% cheaper |
| #24 |
Claude Fable 5
Anthropic
|
$11.604250 (rounded ~ $11.60) | ↓ 98.3% cheaper |
| #25 |
Claude Mythos 5
Anthropic
|
$11.604250 (rounded ~ $11.60) | ↓ 98.3% cheaper |
| #26 |
GPT-5.5
OpenAI
|
$23.208250 (rounded ~ $23.21) | ↓ 96.5% cheaper |
| #27 |
GPT-6 Astra
OpenAI
|
$46.417000 (rounded ~ $46.42) | ↓ 93.1% cheaper |
| #28 |
GPT-6 Astra
OpenAI
|
$46.417000 (rounded ~ $46.42) | ↓ 93.1% cheaper |
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
Gemini 2.5 Pro Google
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Gemini 3.1 Pro Google
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
For marketing teams managing high-volume, brand-consistent visual pipelines, Nano Banana Pro represents a shift in how we approach enterprise-scale asset generation. When you need to push 10,000 marketing images into your creative workflow each month, the primary friction point is no longer just generation speed—it is brand alignment and reliable text rendering.
Nano Banana Pro excels in scenarios where your assets must include specific, legible text—such as localized ad banners, event invitations, or product infographics. Unlike general-purpose models that often struggle with character alignment or font fidelity, this model maintains high precision for integrated design elements. For enterprise architects, the ability to maintain consistency across such a large volume of assets is critical. If your campaign requires reference characters or objects to appear identical across varying environments and angles, this model offers the architectural stability required to prevent the “drift” common in lower-tier generators.
Choosing this model for your 10,000-image campaign is less about finding the cheapest generation and more about reducing the downstream QA and manual editing burden. By getting the text and composition right in the first pass, you eliminate the need for secondary retouching workflows. This is the difference between a prototype-grade tool and a production-ready engine that scales without breaking your brand guidelines.