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 1,000 input tokens and 500 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 |
|---|---|---|---|
| 🏆 |
Ministral 3 (14B)
Mistral AI
|
$0.025975 (rounded ~ $0.03) Best Value | ↓ 100% cheaper |
| 🥈 |
GPT-5.6 Luna
OpenAI
|
$0.026000 (rounded ~ $0.03) | ↓ 100% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.032500 (rounded ~ $0.03) | ↓ 100% cheaper |
| #4 |
Gemini 3.5 Flash-Lite
Google
|
$0.039088 | ↓ 99.9% cheaper |
| #5 |
Gemini 2.5 Flash
Google
|
$0.039088 | ↓ 99.9% cheaper |
| #6 |
GPT-6 Luna
OpenAI
|
$0.051888 (rounded ~ $0.05) | ↓ 99.9% cheaper |
| #7 |
Mistral Large 3
Mistral AI
|
$0.065063 (rounded ~ $0.07) | ↓ 99.9% cheaper |
| #8 |
Gemini 3.8 Flash
Google
|
$0.097406 (rounded ~ $0.10) | ↓ 99.9% cheaper |
| #9 |
Gemini 3.6 Flash
Google
|
$0.097406 (rounded ~ $0.10) | ↓ 99.9% cheaper |
| #10 |
GPT-5.4 mini
OpenAI
|
$0.097500 (rounded ~ $0.10) | ↓ 99.9% cheaper |
| #11 |
Claude Haiku 5.5
Anthropic
|
$0.129875 | ↓ 99.8% cheaper |
| #12 |
Claude Haiku 4.5
Anthropic
|
$0.129875 | ↓ 99.8% cheaper |
| #13 |
Mistral Large 4
Mistral AI
|
$0.176983 (rounded ~ $0.18) | ↓ 99.7% cheaper |
| #14 |
Mistral Medium 3.5
Mistral AI
|
$0.194813 (rounded ~ $0.19) | ↓ 99.7% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.227938 (rounded ~ $0.23) | ↓ 99.7% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.227938 (rounded ~ $0.23) | ↓ 99.7% cheaper |
| #17 |
Llama 4 Maverick (400B)
Meta AI
|
$0.241950 (rounded ~ $0.24) | ↓ 99.6% cheaper |
| #18 |
Claude Sonnet 5.5
Anthropic
|
$0.259750 | ↓ 99.6% cheaper |
| #19 |
Claude Sonnet 5
Anthropic
|
$0.259750 | ↓ 99.6% cheaper |
| #20 |
Gemini 4 Argon
Google
|
$0.259750 | ↓ 99.6% cheaper |
| #21 |
Gemini 3.1 Flash
Google
|
$0.260000 | ↓ 99.6% cheaper |
| #22 |
GPT-5.6 Terra
OpenAI
|
$0.260000 | ↓ 99.6% cheaper |
| #23 |
Claude Sonnet 4.6
Anthropic
|
$0.389625 | ↓ 99.4% cheaper |
| #24 |
Claude Opus 5.5
Anthropic
|
$0.519500 | ↓ 99.2% cheaper |
| #25 |
GPT-5.6 Sol
OpenAI
|
$0.519500 | ↓ 99.2% cheaper |
| #26 |
Claude Opus 4.7
Anthropic
|
$0.649375 | ↓ 99% cheaper |
| #27 |
Claude Opus 5
Anthropic
|
$0.649375 | ↓ 99% cheaper |
| #28 |
Claude Opus 4.8
Anthropic
|
$0.649375 | ↓ 99% cheaper |
| #29 |
Claude Opus 4.6
Anthropic
|
$0.649375 | ↓ 99% cheaper |
| #30 |
Gemini 2.5 Pro
Google
|
$0.650000 | ↓ 99% cheaper |
| #31 |
GPT-5.5 Instant
OpenAI
|
$0.650000 | ↓ 99% cheaper |
| #32 |
Grok 4.3
xAI
|
$1.036000 (rounded ~ $1.04) | ↓ 98.5% cheaper |
| #33 |
GPT-6.1 Sol
OpenAI
|
$1.037750 (rounded ~ $1.04) | ↓ 98.5% cheaper |
| #34 |
GPT-6 Sol
OpenAI
|
$1.037750 (rounded ~ $1.04) | ↓ 98.5% cheaper |
| #35 |
Gemini 3.1 Pro
Google
|
$1.038500 (rounded ~ $1.04) | ↓ 98.5% cheaper |
| #36 |
GPT-5.4
OpenAI
|
$1.298125 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #37 |
GPT-5.4 Thinking
OpenAI
|
$1.298125 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #38 |
Claude Fable 5.1
Anthropic
|
$1.298750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #39 |
Claude Mythos 5.1
Anthropic
|
$1.298750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #40 |
Claude Fable 5
Anthropic
|
$1.298750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #41 |
Claude Mythos 5
Anthropic
|
$1.298750 (rounded ~ $1.30) | ↓ 98.1% cheaper |
| #42 |
GPT-5.5
OpenAI
|
$2.596250 (rounded ~ $2.60) | ↓ 96.1% cheaper |
| #43 |
GPT-5.2 Pro
OpenAI
|
$2.735250 (rounded ~ $2.74) | ↓ 95.9% cheaper |
| #44 |
GPT-5.5 Pro
OpenAI
|
$3.900000 | ↓ 94.2% cheaper |
| #45 |
GPT-6 Astra
OpenAI
|
$5.195000 (rounded ~ $5.20) | ↓ 92.2% cheaper |
| #46 |
GPT-6 Astra
OpenAI
|
$5.195000 (rounded ~ $5.20) | ↓ 92.2% cheaper |
Ministral 3 (14B) Mistral AI
GPT-5.6 Luna OpenAI
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
GPT-6 Luna OpenAI
Mistral Large 3 Mistral AI
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
GPT-5.4 mini OpenAI
Claude Haiku 5.5 Anthropic
Claude Haiku 4.5 Anthropic
Mistral Large 4 Mistral AI
Mistral Medium 3.5 Mistral AI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Llama 4 Maverick (400B) Meta AI
Claude Sonnet 5.5 Anthropic
Claude Sonnet 5 Anthropic
Gemini 4 Argon Google
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 5.5 Anthropic
GPT-5.6 Sol OpenAI
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
Grok 4.3 xAI
GPT-6.1 Sol OpenAI
GPT-6 Sol OpenAI
Gemini 3.1 Pro Google
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
GPT-5.5 OpenAI
GPT-5.2 Pro OpenAI
GPT-5.5 Pro OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
For a newsletter publisher managing a 50K subscriber base, visual identity is non-negotiable. An image generation campaign requires a balance between creative flexibility and output consistency. When scaling to 200 marketing images per week, the primary challenge shifts from individual prompt engineering to maintaining a cohesive brand aesthetic across every asset. Nano Banana Pro offers a specialized pipeline for these high-volume requirements, allowing publishers to move beyond generic stock photography.
The strength of this model lies in its ability to handle varied resolutions without sacrificing detail, which is essential for multi-channel distribution. Whether your workflow demands high-fidelity headers for email newsletters or optimized thumbnails for social media integration, the model’s architecture is tuned to minimize the drift often seen in long-running generation batches. For publishers, this means less time spent on iterative re-prompting and more focus on strategic content layout.
Decision factors for this workload extend beyond raw output. You must consider the latency of the generation pipeline, especially when integrating with automated editorial workflows. While some models prioritize speed, Nano Banana Pro is often preferred for workflows where structural fidelity is the primary constraint. If your newsletter relies on specific brand palettes or complex composition, the investment in a dedicated image-capable model ensures that your visual storytelling remains sharp and professional as your subscriber list grows. By establishing a fixed-cost baseline per thousand images, you can project your quarterly marketing budget with significantly higher confidence.