Nano Banana Pro Google
💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $53.600000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 1,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $53.600000
- Total Cost: $53.600000
- Cost per 1K tokens: $1.050980
- Tokens per dollar: 951 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: 42.68 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
|
$0.006439 (rounded ~ $0.01) Best Value | ↓ 100% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.016284 (rounded ~ $0.02) | ↓ 100% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.019716 | ↓ 100% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.019716 | ↓ 100% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.032443 (rounded ~ $0.03) | ↓ 99.9% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.048664 (rounded ~ $0.05) | ↓ 99.9% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.048851 (rounded ~ $0.05) | ↓ 99.9% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.064635 (rounded ~ $0.06) | ↓ 99.9% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.064885 (rounded ~ $0.06) | ↓ 99.9% cheaper |
| #10 |
GPT-5.6 Luna
OpenAI
|
$0.065135 (rounded ~ $0.07) | ↓ 99.9% cheaper |
| #11 |
o4-mini
OpenAI
|
$0.071099 (rounded ~ $0.07) | ↓ 99.9% cheaper |
| #12 |
Gemini 3.6 Flash
Google
|
$0.097328 (rounded ~ $0.10) | ↓ 99.8% cheaper |
| #13 |
Gemini 3.5 Flash
Google
|
$0.097703 (rounded ~ $0.10) | ↓ 99.8% cheaper |
| #14 |
GPT-5.3 Codex Spark
OpenAI
|
$0.114861 (rounded ~ $0.11) | ↓ 99.8% cheaper |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.114861 (rounded ~ $0.11) | ↓ 99.8% cheaper |
| #16 |
Claude Sonnet 5
Anthropic
|
$0.129770 | ↓ 99.8% cheaper |
| #17 |
Gemini 3.1 Flash
Google
|
$0.130270 | ↓ 99.8% cheaper |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.162838 (rounded ~ $0.16) | ↓ 99.7% cheaper |
| #19 |
Claude Sonnet 4.6
Anthropic
|
$0.194655 (rounded ~ $0.19) | ↓ 99.6% cheaper |
| #20 |
Claude Opus 4.7
Anthropic
|
$0.324425 (rounded ~ $0.32) | ↓ 99.4% cheaper |
| #21 |
Claude Opus 5
Anthropic
|
$0.324425 (rounded ~ $0.32) | ↓ 99.4% cheaper |
| #22 |
Claude Opus 4.8
Anthropic
|
$0.324425 (rounded ~ $0.32) | ↓ 99.4% cheaper |
| #23 |
Claude Opus 4.6
Anthropic
|
$0.324425 (rounded ~ $0.32) | ↓ 99.4% cheaper |
| #24 |
Gemini 2.5 Pro
Google
|
$0.325675 (rounded ~ $0.33) | ↓ 99.4% cheaper |
| #25 |
GPT-5.5 Instant
OpenAI
|
$0.325675 (rounded ~ $0.33) | ↓ 99.4% cheaper |
| #26 |
GPT-5.6 Sol
OpenAI
|
$0.325675 (rounded ~ $0.33) | ↓ 99.4% cheaper |
| #27 |
Grok 4.3
xAI
|
$0.513080 (rounded ~ $0.51) | ↓ 99% cheaper |
| #28 |
Gemini 3.1 Pro
Google
|
$0.518080 (rounded ~ $0.52) | ↓ 99% cheaper |
| #29 |
Claude Fable 5.1
Anthropic
|
$0.605463 (rounded ~ $0.61) | ↓ 98.9% cheaper |
| #30 |
Claude Mythos 5.1
Anthropic
|
$0.605463 (rounded ~ $0.61) | ↓ 98.9% cheaper |
| #31 |
o3 Deep Research
OpenAI
|
$0.646350 (rounded ~ $0.65) | ↓ 98.8% cheaper |
| #32 |
GPT-5.4
OpenAI
|
$0.647600 (rounded ~ $0.65) | ↓ 98.8% cheaper |
| #33 |
GPT-5.4 Thinking
OpenAI
|
$0.647600 (rounded ~ $0.65) | ↓ 98.8% cheaper |
| #34 |
Claude Fable 5
Anthropic
|
$0.648850 (rounded ~ $0.65) | ↓ 98.8% cheaper |
| #35 |
Claude Mythos 5
Anthropic
|
$0.648850 (rounded ~ $0.65) | ↓ 98.8% cheaper |
| #36 |
o3 Pro
OpenAI
|
$1.292700 (rounded ~ $1.29) | ↓ 97.6% cheaper |
| #37 |
GPT-5.5
OpenAI
|
$1.295200 (rounded ~ $1.30) | ↓ 97.6% cheaper |
| #38 |
GPT-5.2 Pro
OpenAI
|
$1.378335 (rounded ~ $1.38) | ↓ 97.4% cheaper |
| #39 |
GPT-6 Astra
OpenAI
|
$2.595400 (rounded ~ $2.60) | ↓ 95.2% cheaper |
| #40 |
GPT-6 Astra
OpenAI
|
$2.595400 (rounded ~ $2.60) | ↓ 95.2% cheaper |
Mistral Small 3 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
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
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
o3 Pro OpenAI
GPT-5.5 OpenAI
GPT-5.2 Pro OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
For marketing teams managing high-volume, repetitive image generation tasks, Nano Banana Pro has emerged as a distinct powerhouse. Unlike general-purpose models that prioritize artistic flair or complex narrative, this model is engineered for utility, speed, and consistency. In a fast-moving marketing environment where you need hundreds of variations for social media, email campaigns, and product mockups, the ability to generate assets without the bottleneck of heavy prompt engineering is a significant operational advantage.
What sets this model apart is its integration-first design. It excels in workflows where visuals are part of a larger, automated document or presentation pipeline. If your campaign requires generating 800 images per month—such as templated product photos or social media graphics—the model’s predictable output and optimized inference speed become more important than stylistic variability. It avoids the ‘hallucinated’ details that often plague larger, more creative models, making it a reliable choice for brand-consistent assets where accuracy and adherence to a defined visual style are non-negotiable.
This model is best suited for teams that value efficiency over creative experimentation. While it may not provide the same depth of artistic nuance found in frontier reasoning models, it offers a level of stability that is hard to find in the current landscape. When your ROI is driven by the sheer speed of asset production and the ability to maintain a consistent visual baseline across thousands of units, this model is the clear choice.