Nano Banana Pro Google
💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $6.700000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 1,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $6.700000
- Total Cost: $6.700000
- Cost per 1K tokens: $0.066337 (rounded ~ $0.07)
- Tokens per dollar: 15,075 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 minute, 24.35 seconds
- Latency: 50 milliseconds to first token
- Base Throughput: 1,200 tokens/second
Best Use Cases
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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💰 Total Cost Calculation (from Plugin)
Output: $0.000000
Output: $0.000000
Unit: $0.100000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 1,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $0.100000
- Total Cost: $0.100000
- Cost per 1K tokens: $0.000990
- Tokens per dollar: 1,010,000 tokens
- Context Window: 65536 tokens
- Thinking Source: (0 tokens)
Speed & Performance Analysis
With a processing speed of 300 tokens per second and 200ms time to first token:
- Processing Time: 5 minutes, 36.85 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 300 tokens/second
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Mistral OCR 3. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.
Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to Nano Banana Pro| Rank | AI Model & Provider | Total Cost | vs Nano Banana Pro | vs Mistral OCR 3 |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.002160 Best Value | ↓ 100% cheaper | ↓ 97.8% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.005586 (rounded ~ $0.01) | ↓ 99.9% cheaper | ↓ 94.4% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.006879 (rounded ~ $0.01) | ↓ 99.9% cheaper | ↓ 93.1% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.006879 (rounded ~ $0.01) | ↓ 99.9% cheaper | ↓ 93.1% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.011048 (rounded ~ $0.01) | ↓ 99.8% cheaper | ↓ 89% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.016571 (rounded ~ $0.02) | ↓ 99.8% cheaper | ↓ 83.4% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.016759 (rounded ~ $0.02) | ↓ 99.7% cheaper | ↓ 83.2% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.021845 (rounded ~ $0.02) | ↓ 99.7% cheaper | ↓ 78.2% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.022095 (rounded ~ $0.02) | ↓ 99.7% cheaper | ↓ 77.9% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.022345 (rounded ~ $0.02) | ↓ 99.7% cheaper | ↓ 77.7% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.022345 (rounded ~ $0.02) | ↓ 99.7% cheaper | ↓ 77.7% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.024030 (rounded ~ $0.02) | ↓ 99.6% cheaper | ↓ 76% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.033143 (rounded ~ $0.03) | ↓ 99.5% cheaper | ↓ 66.9% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.033518 (rounded ~ $0.03) | ↓ 99.5% cheaper | ↓ 66.5% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.039979 | ↓ 99.4% cheaper | ↓ 60% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.039979 | ↓ 99.4% cheaper | ↓ 60% cheaper |
| #17 |
Claude Sonnet 5
Anthropic
|
$0.044190 (rounded ~ $0.04) | ↓ 99.3% cheaper | ↓ 55.8% cheaper |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.055863 (rounded ~ $0.06) | ↓ 99.2% cheaper | ↓ 44.1% cheaper |
| #19 |
Gemini 2.5 Pro
Google
|
$0.057113 (rounded ~ $0.06) | ↓ 99.1% cheaper | ↓ 42.9% cheaper |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.066285 (rounded ~ $0.07) | ↓ 99% cheaper | ↓ 33.7% cheaper |
| #21 |
Grok 4.3
xAI
|
$0.085380 (rounded ~ $0.09) | ↓ 98.7% cheaper | ↓ 14.6% cheaper |
| #22 |
Gemini 3.1 Pro
Google
|
$0.089380 | ↓ 98.7% cheaper | ↓ 10.6% cheaper |
| #23 |
Claude Opus 4.7
Anthropic
|
$0.110475 | ↓ 98.4% cheaper | ↑ 10.5% more |
| #24 |
Claude Opus 5
Anthropic
|
$0.110475 | ↓ 98.4% cheaper | ↑ 10.5% more |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.110475 | ↓ 98.4% cheaper | ↑ 10.5% more |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.110475 | ↓ 98.4% cheaper | ↑ 10.5% more |
| #27 |
GPT-5.4
OpenAI
|
$0.111725 (rounded ~ $0.11) | ↓ 98.3% cheaper | ↑ 11.7% more |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.111725 (rounded ~ $0.11) | ↓ 98.3% cheaper | ↑ 11.7% more |
| #29 |
GPT-5.5 Instant
OpenAI
|
$0.111725 (rounded ~ $0.11) | ↓ 98.3% cheaper | ↑ 11.7% more |
| #30 |
GPT-5.6 Sol
OpenAI
|
$0.111725 (rounded ~ $0.11) | ↓ 98.3% cheaper | ↑ 11.7% more |
| #31 |
Claude Fable 5.1
Anthropic
|
$0.206738 (rounded ~ $0.21) | ↓ 96.9% cheaper | ↑ 106.7% more |
| #32 |
Claude Mythos 5.1
Anthropic
|
$0.206738 (rounded ~ $0.21) | ↓ 96.9% cheaper | ↑ 106.7% more |
| #33 |
o3 Deep Research
OpenAI
|
$0.218450 (rounded ~ $0.22) | ↓ 96.7% cheaper | ↑ 118.5% more |
| #34 |
Claude Fable 5
Anthropic
|
$0.220950 | ↓ 96.7% cheaper | ↑ 121% more |
| #35 |
Claude Mythos 5
Anthropic
|
$0.220950 | ↓ 96.7% cheaper | ↑ 121% more |
| #36 |
GPT-5.5
OpenAI
|
$0.223450 (rounded ~ $0.22) | ↓ 96.7% cheaper | ↑ 123.5% more |
| #37 |
o3 Pro
OpenAI
|
$0.436900 (rounded ~ $0.44) | ↓ 93.5% cheaper | ↑ 336.9% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.441900 (rounded ~ $0.44) | ↓ 93.4% cheaper | ↑ 341.9% more |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.479745 | ↓ 92.8% cheaper | ↑ 379.7% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.479745 | ↓ 92.8% cheaper | ↑ 379.7% more |
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
Gemini 3.1 Flash Google
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
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Gemini 3.1 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Choosing the Right Pipeline for Visual Automation
When building an automated pipeline for product image variations, the choice of model hinges on the specific nature of your catalog. While both Nano Banana Pro and Mistral OCR 3 handle image-based tasks, they serve distinct roles in a modern e-commerce stack. Understanding these differences is the difference between a high-converting catalog and a pipeline that requires constant manual correction.
Nano Banana Pro is your go-to for creative, lifestyle-oriented variations. If your goal is to place a product in diverse settings—such as moving from a studio white-background shot to an aspirational kitchen or outdoor environment—this model excels at generating the environmental context while preserving the product’s core identity. It is optimized for the visual nuances that capture consumer interest, making it the preferred choice for marketing assets and social media campaigns where emotional resonance is the primary objective.
Conversely, Mistral OCR 3 shines when your variations require high-precision handling of text, labels, and structured components. If your product variations involve generating images that must include accurate, readable text—such as product packaging, instructional labels, or detailed specification sheets—the OCR-integrated capabilities of this model provide a significant edge. It reduces the common AI failure point of broken or hallucinated text, ensuring that the generated variations meet technical and compliance standards. By pairing these models correctly based on whether your variation task is primarily lifestyle-driven or information-heavy, you can build a more resilient and versatile automated creative engine that scales with your inventory.