Nano Banana Pro Google
💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $67.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500 input tokens and 1,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $67.000000
- Total Cost: $67.000000
- Cost per 1K tokens: $44.666667 (rounded ~ $44.67)
- Tokens per dollar: 22 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: 1.43 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 |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.012988 (rounded ~ $0.01) Best Value | ↓ 100% cheaper |
| 🥈 |
Ministral 3 (14B)
Mistral AI
|
$0.025975 (rounded ~ $0.03) | ↓ 100% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.032656 (rounded ~ $0.03) | ↓ 100% cheaper |
| #4 |
Gemini 3.5 Flash-Lite
Google
|
$0.039363 | ↓ 99.9% cheaper |
| #5 |
Gemini 2.5 Flash
Google
|
$0.039363 | ↓ 99.9% cheaper |
| #6 |
Mistral Large 3
Mistral AI
|
$0.065188 (rounded ~ $0.07) | ↓ 99.9% cheaper |
| #7 |
Gemini 3.8 Flash
Google
|
$0.097781 (rounded ~ $0.10) | ↓ 99.9% cheaper |
| #8 |
GPT-5.4 mini
OpenAI
|
$0.097969 (rounded ~ $0.10) | ↓ 99.9% cheaper |
| #9 |
o4-mini Deep Research
OpenAI
|
$0.130125 | ↓ 99.8% cheaper |
| #10 |
Claude Haiku 4.5
Anthropic
|
$0.130375 | ↓ 99.8% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.130625 | ↓ 99.8% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.143138 (rounded ~ $0.14) | ↓ 99.8% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.195563 (rounded ~ $0.20) | ↓ 99.7% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.195938 (rounded ~ $0.20) | ↓ 99.7% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.229469 | ↓ 99.7% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.229469 | ↓ 99.7% cheaper |
| #17 |
Llama 4 Maverick (400B)
Meta AI
|
$0.242175 (rounded ~ $0.24) | ↓ 99.6% cheaper |
| #18 |
Claude Sonnet 5
Anthropic
|
$0.260750 | ↓ 99.6% cheaper |
| #19 |
Gemini 3.1 Flash
Google
|
$0.261250 (rounded ~ $0.26) | ↓ 99.6% cheaper |
| #20 |
GPT-5.6 Terra
OpenAI
|
$0.326563 (rounded ~ $0.33) | ↓ 99.5% cheaper |
| #21 |
Claude Sonnet 4.6
Anthropic
|
$0.391125 (rounded ~ $0.39) | ↓ 99.4% cheaper |
| #22 |
Claude Opus 4.7
Anthropic
|
$0.651875 (rounded ~ $0.65) | ↓ 99% cheaper |
| #23 |
Claude Opus 5
Anthropic
|
$0.651875 (rounded ~ $0.65) | ↓ 99% cheaper |
| #24 |
Claude Opus 4.8
Anthropic
|
$0.651875 (rounded ~ $0.65) | ↓ 99% cheaper |
| #25 |
Claude Opus 4.6
Anthropic
|
$0.651875 (rounded ~ $0.65) | ↓ 99% cheaper |
| #26 |
Gemini 2.5 Pro
Google
|
$0.653125 (rounded ~ $0.65) | ↓ 99% cheaper |
| #27 |
GPT-5.5 Instant
OpenAI
|
$0.653125 (rounded ~ $0.65) | ↓ 99% cheaper |
| #28 |
GPT-5.6 Sol
OpenAI
|
$0.653125 (rounded ~ $0.65) | ↓ 99% cheaper |
| #29 |
Grok 4.3
xAI
|
$1.037000 (rounded ~ $1.04) | ↓ 98.5% cheaper |
| #30 |
Gemini 3.1 Pro
Google
|
$1.042000 (rounded ~ $1.04) | ↓ 98.4% cheaper |
| #31 |
o3 Deep Research
OpenAI
|
$1.301250 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #32 |
GPT-5.4
OpenAI
|
$1.302500 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #33 |
GPT-5.4 Thinking
OpenAI
|
$1.302500 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #34 |
Claude Fable 5.1
Anthropic
|
$1.303750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #35 |
Claude Mythos 5.1
Anthropic
|
$1.303750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #36 |
Claude Fable 5
Anthropic
|
$1.303750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #37 |
Claude Mythos 5
Anthropic
|
$1.303750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #38 |
o3 Pro
OpenAI
|
$2.602500 (rounded ~ $2.60) | ↓ 96.1% cheaper |
| #39 |
GPT-5.5
OpenAI
|
$2.605000 (rounded ~ $2.61) | ↓ 96.1% cheaper |
| #40 |
GPT-5.2 Pro
OpenAI
|
$2.753625 (rounded ~ $2.75) | ↓ 95.9% cheaper |
| #41 |
GPT-5.5 Pro
OpenAI
|
$3.918750 (rounded ~ $3.92) | ↓ 94.2% cheaper |
| #42 |
GPT-6 Astra
OpenAI
|
$5.215000 (rounded ~ $5.22) | ↓ 92.2% cheaper |
| #43 |
GPT-6 Astra
OpenAI
|
$5.215000 (rounded ~ $5.22) | ↓ 92.2% cheaper |
Mistral Small 3 Mistral AI
Ministral 3 (14B) Mistral AI
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Llama 4 Maverick (400B) Meta AI
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-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Gemini 3.1 Pro Google
o3 Deep Research OpenAI
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
o3 Pro OpenAI
GPT-5.5 OpenAI
GPT-5.2 Pro OpenAI
GPT-5.5 Pro OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
For e-commerce teams managing thousands of SKUs, the ability to generate diverse product variations—such as lifestyle scenes, different backgrounds, or seasonal settings—from a single base image has become a critical operational requirement. Relying on traditional photography for every variation is prohibitively expensive and slow, creating a bottleneck in seasonal campaigns and marketplace expansions. Nano Banana Pro has emerged as a high-efficiency solution for these specific image-generation workloads.
This model is designed to handle visual synthesis tasks where consistency and speed are paramount. Unlike general-purpose models that may struggle with maintaining product fidelity across multiple variations, Nano Banana Pro excels in preserving the core identity of the product while modifying the environment and lighting. This is particularly valuable for brands that need to quickly generate high-fidelity assets for ad testing, A/B testing, or marketplace-specific visual requirements.
When evaluating this model for your image-generation pipeline, focus on how it balances creative flexibility with brand consistency. For teams scaling their creative operations, the model’s ability to ingest base product images and output multiple high-quality iterations in a single batch can significantly reduce the time from ideation to deployment. By focusing on models that support native image generation, you bypass the friction of text-only model workflows, ensuring your visual assets meet the demanding standards of modern e-commerce platforms.