Gemini 3.6 Flash Google 1048576
$0.027188 (rounded ~ $0.03)
Total Cost
Vision/Images
✓ Available
Audio Processing
✓ Available
Video Analysis
✓ Available
Tool Usage
✓ Available
OCR Support
✗ Not Available
Batch API
✓ Available
Caching
✓ Available
90% savings
💰 Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.094688 (rounded ~ $0.09)
Input: $0.093750 (rounded ~ $0.09)
Output: $0.000938
Output: $0.000938
Optimized Cost
$0.027188 (rounded ~ $0.03)
Input: $0.093750 (rounded ~ $0.09)
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Total Savings
$0.067500 (rounded ~ $0.07)
71.3% discount
Advanced Cost Breakdown (from Plugin)
📊 Batch API
50.0% off
Asynchronous processing discount
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 1,000 output tokens:
- Input Cost: $0.093750 (rounded ~ $0.09)
- Output Cost: $0.000938
- Total Cost: $0.027188 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000054
- Tokens per dollar: 18,427,586 tokens
- Context Window: 1048576 tokens
Speed & Performance Analysis
With a processing speed of 304 tokens per second and 120ms time to first token:
- Processing Time: 28 minutes, 1.17 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 304 tokens/second
- Effective Throughput: 298 tokens/second (temperature-adjusted)
Best Use Cases
High-throughput document summarization and extraction for massive enterprise archives where consistency and cost-efficiency are paramount.
Want this applied to YOUR actual stack?
This calculator shows the math for Gemini 3.6 Flash. 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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← Back to Gemini 3.6 Flash
📋 Active Input Parameters
Input Tokens:
500,000
Output Tokens:
1,000
Batch API:
Enabled (50% discount)
Cached Tokens:
80%
Tools:
Enabled
| Rank | AI Model & Provider | Total Cost | vs Gemini 3.6 Flash |
|---|---|---|---|
| 🏆 |
GPT-5.6 Luna
OpenAI
|
$0.007300 (rounded ~ $0.01) Best Value | ↓ 73.1% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.009125 | ↓ 66.4% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.011125 (rounded ~ $0.01) | ↓ 59.1% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.011125 (rounded ~ $0.01) | ↓ 59.1% cheaper |
| #5 |
GPT-6 Luna
OpenAI
|
$0.014375 (rounded ~ $0.01) | ↓ 47.1% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.027188 (rounded ~ $0.03) | Same price |
| #7 |
Claude Haiku 5.5
Anthropic
|
$0.036250 (rounded ~ $0.04) | ↑ 33.3% more |
| #8 |
Mistral Large 4
Mistral AI
|
$0.048645 (rounded ~ $0.05) | ↑ 78.9% more |
| #9 |
Claude Sonnet 5.5
Anthropic
|
$0.062500 (rounded ~ $0.06) | ↑ 129.9% more |
| #10 |
Gemini 4 Argon
Google
|
$0.072500 (rounded ~ $0.07) | ↑ 166.7% more |
| #11 |
Claude Sonnet 5
Anthropic
|
$0.072500 (rounded ~ $0.07) | ↑ 166.7% more |
| #12 |
Gemini 3.1 Flash
Google
|
$0.073000 (rounded ~ $0.07) | ↑ 168.5% more |
| #13 |
GPT-5.6 Terra
OpenAI
|
$0.073000 (rounded ~ $0.07) | ↑ 168.5% more |
| #14 |
Claude Sonnet 4.6
Anthropic
|
$0.108750 (rounded ~ $0.11) | ↑ 300% more |
| #15 |
Claude Opus 5.5
Anthropic
|
$0.125000 (rounded ~ $0.13) | ↑ 359.8% more |
| #16 |
GPT-5.6 Sol
OpenAI
|
$0.145000 (rounded ~ $0.15) | ↑ 433.3% more |
| #17 |
Claude Opus 4.7
Anthropic
|
$0.181250 (rounded ~ $0.18) | ↑ 566.7% more |
| #18 |
Claude Opus 5
Anthropic
|
$0.181250 (rounded ~ $0.18) | ↑ 566.7% more |
| #19 |
Claude Opus 4.8
Anthropic
|
$0.181250 (rounded ~ $0.18) | ↑ 566.7% more |
| #20 |
Claude Opus 4.6
Anthropic
|
$0.181250 (rounded ~ $0.18) | ↑ 566.7% more |
| #21 |
Gemini 2.5 Pro
Google
|
$0.182500 (rounded ~ $0.18) | ↑ 571.3% more |
| #22 |
Grok 4.3
xAI
|
$0.284000 (rounded ~ $0.28) | ↑ 944.6% more |
| #23 |
Grok 4.20 Beta
xAI
|
$0.284000 (rounded ~ $0.28) | ↑ 944.6% more |
| #24 |
GPT-6.1 Sol
OpenAI
|
$0.287500 (rounded ~ $0.29) | ↑ 957.5% more |
| #25 |
GPT-6 Sol
OpenAI
|
$0.287500 (rounded ~ $0.29) | ↑ 957.5% more |
| #26 |
Claude Fable 5.1
Anthropic
|
$0.287500 (rounded ~ $0.29) | ↑ 957.5% more |
| #27 |
Claude Mythos 5.1
Anthropic
|
$0.287500 (rounded ~ $0.29) | ↑ 957.5% more |
| #28 |
Gemini 3.1 Pro
Google
|
$0.289000 (rounded ~ $0.29) | ↑ 963% more |
| #29 |
GPT-5.4
OpenAI
|
$0.361250 (rounded ~ $0.36) | ↑ 1228.7% more |
| #30 |
GPT-5.4 Thinking
OpenAI
|
$0.361250 (rounded ~ $0.36) | ↑ 1228.7% more |
| #31 |
Claude Fable 5
Anthropic
|
$0.362500 (rounded ~ $0.36) | ↑ 1233.3% more |
| #32 |
Claude Mythos 5
Anthropic
|
$0.362500 (rounded ~ $0.36) | ↑ 1233.3% more |
| #33 |
GPT-5.5
OpenAI
|
$0.722500 (rounded ~ $0.72) | ↑ 2557.5% more |
| #34 |
GPT-6 Astra
OpenAI
|
$1.450000 | ↑ 5233.3% more |
| #35 |
GPT-6 Astra
OpenAI
|
$1.450000 | ↑ 5233.3% more |
🏆
GPT-5.6 Luna
GPT-5.6 Luna OpenAI
$0.007300 (rounded ~ $0.01)
vs Gemini 3.6 Flash:
↓ 73.1%
🥈
Gemini 3.1 Flash Lite
Gemini 3.1 Flash Lite Google
$0.009125
vs Gemini 3.6 Flash:
↓ 66.4%
🥉
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite Google
$0.011125 (rounded ~ $0.01)
vs Gemini 3.6 Flash:
↓ 59.1%
#4
Gemini 2.5 Flash
Gemini 2.5 Flash Google
$0.011125 (rounded ~ $0.01)
vs Gemini 3.6 Flash:
↓ 59.1%
#5
GPT-6 Luna
GPT-6 Luna OpenAI
$0.014375 (rounded ~ $0.01)
vs Gemini 3.6 Flash:
↓ 47.1%
#6
Gemini 3.8 Flash
Gemini 3.8 Flash Google
$0.027188 (rounded ~ $0.03)
vs Gemini 3.6 Flash:
Same
#7
Claude Haiku 5.5
Claude Haiku 5.5 Anthropic
$0.036250 (rounded ~ $0.04)
vs Gemini 3.6 Flash:
↑ 33.3%
#8
Mistral Large 4
Mistral Large 4 Mistral AI
$0.048645 (rounded ~ $0.05)
vs Gemini 3.6 Flash:
↑ 78.9%
#9
Claude Sonnet 5.5
Claude Sonnet 5.5 Anthropic
$0.062500 (rounded ~ $0.06)
vs Gemini 3.6 Flash:
↑ 129.9%
#10
Gemini 4 Argon
Gemini 4 Argon Google
$0.072500 (rounded ~ $0.07)
vs Gemini 3.6 Flash:
↑ 166.7%
#11
Claude Sonnet 5
Claude Sonnet 5 Anthropic
$0.072500 (rounded ~ $0.07)
vs Gemini 3.6 Flash:
↑ 166.7%
#12
Gemini 3.1 Flash
Gemini 3.1 Flash Google
$0.073000 (rounded ~ $0.07)
vs Gemini 3.6 Flash:
↑ 168.5%
#13
GPT-5.6 Terra
GPT-5.6 Terra OpenAI
$0.073000 (rounded ~ $0.07)
vs Gemini 3.6 Flash:
↑ 168.5%
#14
Claude Sonnet 4.6
Claude Sonnet 4.6 Anthropic
$0.108750 (rounded ~ $0.11)
vs Gemini 3.6 Flash:
↑ 300%
#15
Claude Opus 5.5
Claude Opus 5.5 Anthropic
$0.125000 (rounded ~ $0.13)
vs Gemini 3.6 Flash:
↑ 359.8%
#16
GPT-5.6 Sol
GPT-5.6 Sol OpenAI
$0.145000 (rounded ~ $0.15)
vs Gemini 3.6 Flash:
↑ 433.3%
#17
Claude Opus 4.7
Claude Opus 4.7 Anthropic
$0.181250 (rounded ~ $0.18)
vs Gemini 3.6 Flash:
↑ 566.7%
#18
Claude Opus 5
Claude Opus 5 Anthropic
$0.181250 (rounded ~ $0.18)
vs Gemini 3.6 Flash:
↑ 566.7%
#19
Claude Opus 4.8
Claude Opus 4.8 Anthropic
$0.181250 (rounded ~ $0.18)
vs Gemini 3.6 Flash:
↑ 566.7%
#20
Claude Opus 4.6
Claude Opus 4.6 Anthropic
$0.181250 (rounded ~ $0.18)
vs Gemini 3.6 Flash:
↑ 566.7%
#21
Gemini 2.5 Pro
Gemini 2.5 Pro Google
$0.182500 (rounded ~ $0.18)
vs Gemini 3.6 Flash:
↑ 571.3%
#22
Grok 4.3
Grok 4.3 xAI
$0.284000 (rounded ~ $0.28)
vs Gemini 3.6 Flash:
↑ 944.6%
#23
Grok 4.20 Beta
Grok 4.20 Beta xAI
$0.284000 (rounded ~ $0.28)
vs Gemini 3.6 Flash:
↑ 944.6%
#24
GPT-6.1 Sol
GPT-6.1 Sol OpenAI
$0.287500 (rounded ~ $0.29)
vs Gemini 3.6 Flash:
↑ 957.5%
#25
GPT-6 Sol
GPT-6 Sol OpenAI
$0.287500 (rounded ~ $0.29)
vs Gemini 3.6 Flash:
↑ 957.5%
#26
Claude Fable 5.1
Claude Fable 5.1 Anthropic
$0.287500 (rounded ~ $0.29)
vs Gemini 3.6 Flash:
↑ 957.5%
#27
Claude Mythos 5.1
Claude Mythos 5.1 Anthropic
$0.287500 (rounded ~ $0.29)
vs Gemini 3.6 Flash:
↑ 957.5%
#28
Gemini 3.1 Pro
Gemini 3.1 Pro Google
$0.289000 (rounded ~ $0.29)
vs Gemini 3.6 Flash:
↑ 963%
#29
GPT-5.4
GPT-5.4 OpenAI
$0.361250 (rounded ~ $0.36)
vs Gemini 3.6 Flash:
↑ 1228.7%
#30
GPT-5.4 Thinking
GPT-5.4 Thinking OpenAI
$0.361250 (rounded ~ $0.36)
vs Gemini 3.6 Flash:
↑ 1228.7%
#31
Claude Fable 5
Claude Fable 5 Anthropic
$0.362500 (rounded ~ $0.36)
vs Gemini 3.6 Flash:
↑ 1233.3%
#32
Claude Mythos 5
Claude Mythos 5 Anthropic
$0.362500 (rounded ~ $0.36)
vs Gemini 3.6 Flash:
↑ 1233.3%
#33
GPT-5.5
GPT-5.5 OpenAI
$0.722500 (rounded ~ $0.72)
vs Gemini 3.6 Flash:
↑ 2557.5%
#34
GPT-6 Astra
GPT-6 Astra OpenAI
$1.450000
vs Gemini 3.6 Flash:
↑ 5233.3%
#35
GPT-6 Astra
GPT-6 Astra OpenAI
$1.450000
vs Gemini 3.6 Flash:
↑ 5233.3%
✨ How recommendations work (v8.6.0): We scan all active models in the registry and only include those that support ALL your current inputs. For token-based models, we check if they can handle your token counts. For special pricing models (OCR, video, audio), we verify they have the correct pricing structure. Features marked requested were in your inputs but not supported by that model. Now using official provider pricing without reseller markups.
Summarizing high-volume document archives is a cornerstone of modern enterprise intelligence. For teams handling 1 million PDFs per month, the challenge isn’t just the sheer scale—it’s maintaining consistency and accuracy across diverse document types like legal contracts, financial reports, and technical manuals. Gemini 3.6 Flash is engineered specifically for these high-throughput, latency-sensitive environments. Because it supports massive context windows, it allows for end-to-end processing of long-form documents without aggressive chunking, which often loses critical structural context or cross-page references.
When you are processing documents at this scale, the primary bottleneck is often the trade-off between reasoning depth and system latency. Gemini 3.6 Flash excels here by providing a robust balance, allowing your team to move away from simple keyword-based extraction toward genuine semantic understanding. This model is particularly effective for workflows that require consistent, repeatable summarization of complex layouts, such as extracting clauses from contracts or identifying key metrics in quarterly earnings reports. By choosing a model optimized for high-volume, long-context pipelines, you minimize the risk of ‘context loss’ that typically plagues older generation systems. For organizations where document processing is the lifeblood of operations—from legal discovery to supply chain management—this model serves as a reliable, cost-efficient backbone for scaling your AI-driven insights without sacrificing the granular detail required for enterprise decision-making.
Frequently Asked Questions
How accurate are these AI model cost calculations?
Our calculations are based on official pricing from each provider (Google, OpenAI, Anthropic, Meta, xAI, Perplexity, DeepSeek, Mistral) and are updated regularly.
We account for all factors including multimodal inputs, caching discounts, batch API pricing, tool usage multipliers, OCR processing, audio minutes, silence fees, and research mode pricing.
Note: Reseller markups and dedicated instance multipliers have been removed to reflect official provider pricing.
How does prompt caching work?
Caching discounts vary by provider: Google and OpenAI offer 90% discounts on cached input tokens. Anthropic uses write (1.25x) and read (0.10x) multipliers. Savings are applied to the token portion only, not unit-based fees.
How do Market Recommendations work (v8.6.0)?
Our recommendation engine scans the entire model registry and only includes models that support ALL your current input parameters (tokens, images, video, audio, OCR, tools, batch API, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options that can handle your complete workflow. Special pricing models (OCR, video, audio, image generation) are properly handled and only appear when their specific input types are requested. v8.6.0 removes reseller markups (20% buffer) and dedicated instance multipliers to reflect official provider pricing.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 50+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), provides optimization recommendations, and now offers intelligent market matching to find the best alternatives for your specific needs.