🖼️ 10000 Image (Medium)
⚡ 50% Cached
📊 Batch API
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available
📄
OCR Support
✓ Available
⚡
Caching
✗ Not Available
💰
Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.200000
Input: $0.000000
Output: $0.000000
Optimized Cost
$0.100000
Input: $0.000000
Output: $0.000000
Unit: $0.100000
Fees: $0.000000
Total Savings
$0.100000
50.0% discount
Advanced Cost Breakdown (from Plugin)
📄 OCR Processing
$0.200000
100 pages
📊 Batch API
50.0% off
Asynchronous processing discount
Detailed Cost Analysis (from Plugin)
For 5,000,000 input tokens and 2,000 output tokens:
- Input Cost: $0.000000
- Output Cost: $0.000000
- Unit Cost: $0.100000
- Total Cost: $0.100000
- Cost per 1K tokens: $0.000020
- Tokens per dollar: 50,020,000 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: 4 hours, 37 minutes, 53.51 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 300 tokens/second
Best Use Cases
Choose Mistral OCR 3 for layout-sensitive tasks like archival digitization and complex document parsing. Select Gemini 3.1 Flash Lite for general-purpose multimodal extraction at high speed and throughput.
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.
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⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
🖼️ 10000 Image (Medium)
⚡ 50% Cached
📊 Batch API
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✓ Available
🎥
Video Analysis
✓ Available
📄
OCR Support
✓ Available
⚡
Caching
✓ Available
90% savings
💰
Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.635750 (rounded ~ $0.64)
Input: $0.635000 (rounded ~ $0.64)
Output: $0.000750
Optimized Cost
$0.350000
Input: $0.635000 (rounded ~ $0.64)
Output: $0.000750
Unit: $0.000000
Fees: $0.000000
Total Savings
$0.285750 (rounded ~ $0.29)
44.9% discount
Advanced Cost Breakdown (from Plugin)
🖼️ Multimodal Input
$0.000000
5,160,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount
Multimodal Input Details
🖼️ Images
Count: 10000
Resolution: Medium
Tokens: 5,160,000
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 5,000,000 input tokens and 2,000 output tokens:
- Input Cost: $0.635000 (rounded ~ $0.64)
- Output Cost: $0.000750
- Total Cost: $0.350000
- Cost per 1K tokens: $0.000034
- Tokens per dollar: 29,034,286 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 1,000 tokens per second and 80ms time to first token:
- Processing Time: 2 hours, 52 minutes, 45.42 seconds
- Latency: 80 milliseconds to first token
- Base Throughput: 1,000 tokens/second
- Effective Throughput: 980 tokens/second (temperature-adjusted)
Best Use Cases
Choose Mistral OCR 3 for layout-sensitive tasks like archival digitization and complex document parsing. Select Gemini 3.1 Flash Lite for general-purpose multimodal extraction at high speed and throughput.
Want this applied to YOUR actual stack?
This calculator shows the math for Gemini 3.1 Flash Lite. 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 →
🔍
No Alternatives Found
No other models in the registry support all your current input parameters.
Try adjusting some parameters to see more options.
Remove Images
Remove Video
Remove Audio
Remove OCR
Remove Tools
✨ 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.
Digitizing legacy archives requires a balance between accuracy and throughput. When processing 10,000 scanned pages monthly, the choice between Mistral OCR 3 and Gemini 3.1 Flash Lite often comes down to your specific document architecture and downstream processing needs.
Mistral OCR 3 is built from the ground up for high-fidelity document understanding. It excels at preserving complex layouts, such as multi-column reports, scientific tables, and technical manuals. If your archives contain dense, handwritten annotations or deeply nested document structures that require faithful reconstruction, Mistral OCR 3’s ability to output structured metadata—like heading levels and table cell relationships—is a significant advantage. It is designed to act as a foundational layer, ensuring your extracted data maintains its original context, which is vital for long-term archival integrity.
Gemini 3.1 Flash Lite, by contrast, is a workhorse for high-volume, cost-efficient multimodal extraction. While it performs admirably on standard document parsing, its primary strength lies in its speed and its integration into wider, agentic workflows. If your pipeline involves not just extraction but also categorization, summarization, or routing of the extracted data across various applications, Gemini 3.1 Flash Lite’s rapid inference makes it a highly scalable choice. It is particularly well-suited for organizations that prioritize low latency and throughput for standardized document types, like simple forms, receipts, or recurring business correspondence, where getting the data into a usable format quickly is the priority.
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 are image tokens calculated?
Images are tokenized based on resolution: Low: 85 tokens, Medium: 170 tokens, High: 255 tokens, Full: 765 tokens per image. Some models (like Llama 4 Maverick) use tile-based encoding with 1,610 tokens/image (standard) or 8,050 tokens/image (high-res).
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.
