Real-time Multimodal Medical Diagnostic Cost 2026

gpt-5 vs gemini-3-pro
Complete Comparison: 63,595 input tokens × 5,000 output tokens
Comparison Mode (Custom field comparison)
🖼️ 5 Images 🎥 180s Video

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 5 Images, 180s Video.

🖼️ Multimodal Input
Comparison Criteria gpt-5
OpenAI
gemini-3-pro
Google
Input Parameters Applied (5 images, 180s video)
Input Tokens 63,595 63,595
Output Tokens 5,000 5,000
Calculation Results
Input Cost $0.120321 Best $0.127190 (rounded ~ 0.13) Worst
Output Cost $0.070000 Worst $0.060000 Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $0.240321 Most Expensive $0.237190 (rounded ~ 0.24) Best Value
Processing Time 2 minutes, 45.00 seconds Slowest 2 minutes, 18.00 seconds Fastest
Tokens per Second 450 Slowest 500 Fastest
Time to First Token 200ms 200ms
Cost per 1K tokens $0.003258 (rounded ~ 0.00) Best $0.003458 (rounded ~ 0.00) Worst
Tokens per Dollar 306,902 Best Value 289,199 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.750000 Best $2.000000 Worst
Output Cost / 1M (Base) $14.000000 Worst $12.000000 Best
Input Cost / 1M (Optimized) $1.750000 Best
Optimizations: No optimizations applied
$2.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $14.000000 Worst
Optimizations: No optimizations applied
$12.000000 Best
Optimizations: No optimizations applied
Capabilities
Images Support
5 images
✓ Supported ✗ Not Supported
Video Support
180 seconds
✗ Not Supported ✗ Not Supported
Caching Support ✓ Supported ✗ Not Supported
Batch API Support Available ✗ Not Supported
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
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Second Model

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Select AI Model

Gpt 5
OpenAIMax Context: 400,000 tokens
Input: $1.750000 / 1M
Output: $14.000000 / 1M

Calculate Token Costs

▼
▼
Provider-specific multipliers applied after all calculations
Enable for Haiku 4.5 hard cap bypass
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.
Multiply total cost by quantity for project budgeting
$0.240321Total Cost
$0.120321Input Cost
$0.070000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
73,755Total Tokens
$0.003258Cost per 1K
306,902Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
2m 45sProcessing Time
450Tokens/Second
200msTime to First Token
446Effective Speed

Model Comparison

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Model Information

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🔄 Advanced Options

⚡ Optimization
0%
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data (Pro: $4.50/1M/hr, Flash: $1.00/1M/hr)
First 50 hours free, $0.05/hour after (reset at 00:00 UTC)
🧠 Specialized Modes
Enable Thinking Mode (Google models)
Manual thinking tokens (billed at output rate, disabled by default)
Adaptive thinking token estimation for DeepSeek models
30% output surcharge (Vertex AI priority)
Billed at output rate × reasoning multiplier
Global 2x multiplier for priority processing
Enable Reasoning/Thinking Mode (DeepSeek R1, Grok Deep Reason)
Enable Agentic Swarm
🔧 Automated Service Fees
Enable for DeepSeek V4 ($0.01 per 1M tokens)
Enable code execution (adds $0.05 flat fee)
$0.01 per query (auto-applied based on Search Queries input)
🤖 xAI Agent Tools (Unified $5.00/1k)
Real-time X data access calls
Standard internet search calls
Python sandbox execution calls (overrides flat fee if set)
📚 xAI RAG Tools (Unified $2.50/1k)
File search tool access
Collections/RAG knowledge base access - aggregated with File Search at $2.50/1k
ℹ️ Updated xAI Tool Pricing: Agent tools (web, X, code) at $5.00/1k calls. RAG tools (collections, file) at $2.50/1k calls. Integer code_execution_calls overrides boolean.
🎤 Realtime Audio & Deep Research
Enable Deep Research ($2.00/$8.00 rates)
Session length for billing ($0.01 per minute, rounded up)
Active speech time within session
📄 Mistral AI - Unit-Based Options
Number of pages to process with OCR (tiered pricing auto-applied)
Enable HTML table reconstruction surcharge
Duration-based audio processing (not token-based)
Enable speaker diarization (Voxtral models only)
Enable context biasing (Voxtral models only)
🔬 Research & Citation
Enable research tier pricing ($2.00/$8.00 + $0.005/query)
Enable reasoning with 1,000 token floor ($0.015 min)
Fee per source cited when research mode is enabled
⚙️ Performance Tuning
Low = Fast
High = Creative
📊 Advanced Cost Breakdown
📊 Multiple Models Detected: This page contains data for 2 models. See the detailed comparison table above, and switch between models using tabs below.

gpt-5 OpenAI

$0.240321
Total Cost
🖼️ 5 Image (Full) 🎥 180s Video (720p) 🔧 Tools
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation

Base Cost (No Optimizations) $0.240321 Input: $0.120321
Output: $0.070000
Optimized Cost $0.240321 Input: $0.120321
Output: $0.070000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

🖼️ Multimodal Input
$0.000000
5,160 tokens
💻 Code Execution
$0.050000
Flat fee per execution

Multimodal Input Details

🖼️ Images
Count: 5
Resolution: Full
Tokens: 5,160
Cost: $0.000000

Detailed Cost Analysis

For 63,595 input tokens and 5,000 output tokens:

  • Input Cost: $0.120321
  • Output Cost: $0.070000
  • Service Fees: $0.050000
  • Total Cost: $0.240321
  • Cost per 1K tokens: $0.003258 (rounded ~ 0.00)
  • Tokens per dollar: 306,902 tokens
  • Context Window: 400000 tokens

Speed & Performance Analysis

With a processing speed of 450 tokens per second and 200ms time to first token:

  • Processing Time: 2 minutes, 45.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 446 tokens/second (temperature-adjusted)

Best Use Cases

HealthcareTelemedicineDiagnosticsSurgical Assistance

gemini-3-pro Google 2000000

$0.237190 (rounded ~ 0.24)
Total Cost
🖼️ 5 Image (Full) 🎥 180s Video (720p) 🔧 Tools
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available
📄
OCR Support
✗ Not Available
📊
Batch API
✗ Not Available
⚡
Caching
✗ Not Available

💰 Total Cost Calculation

Base Cost (No Optimizations) $0.237190 (rounded ~ 0.24) Input: $0.127190 (rounded ~ 0.13)
Output: $0.060000
Optimized Cost $0.237190 (rounded ~ 0.24) Input: $0.127190 (rounded ~ 0.13)
Output: $0.060000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 63,595 input tokens and 5,000 output tokens:

  • Input Cost: $0.127190 (rounded ~ 0.13)
  • Output Cost: $0.060000
  • Service Fees: $0.050000
  • Total Cost: $0.237190 (rounded ~ 0.24)
  • Cost per 1K tokens: $0.003458 (rounded ~ 0.00)
  • Tokens per dollar: 289,199 tokens
  • Context Window: 2000000 tokens

Speed & Performance Analysis

With a processing speed of 500 tokens per second and 200ms time to first token:

  • Processing Time: 2 minutes, 18.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 495 tokens/second (temperature-adjusted)

Best Use Cases

HealthcareTelemedicineDiagnosticsSurgical Assistance

Healthcare AI Unit Economics & Diagnostic Infrastructure Costs

Complete cost analysis for real-time diagnostic assistance systems combining live video feeds, comprehensive patient history, and high-resolution medical imaging. This 2026 analysis covers the premium pricing for latency-sensitive healthcare applications where sub-second response times can impact patient outcomes and clinical workflows.

Diagnostic Setup & Medical Parameters

  • Live Video Feed: 180 seconds of 4K surgical/clinical footage
  • Video Tokenization: 47,340 tokens (263 per second at 4K resolution)
  • Patient Records: 15,000 text tokens including history and vitals
  • MRI/X-ray Scans: 5 high-res medical images (255 tokens each at full resolution)
  • Total Input: ~63,595 tokens including multimodal components
  • Latency Target: Sub-500ms critical for real-time surgical assistance
  • Reasoning Budget: High accuracy mode with minimal temperature (0.1)
  • Tool Usage: Enabled for medical database integration and protocol checking

Clinical Use Cases & Healthcare ROI

Surgical assistance and guidance systems, emergency room triage automation, remote specialist consultation platforms, diagnostic screening at scale. This calculator helps healthcare administrators budget for AI diagnostic infrastructure, comparing GPT-5’s vision capabilities against Gemini 3 Pro’s integrated multimodal processing. Includes analysis of caching benefits for repeated diagnostic patterns and batch processing for non-emergency cases.

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.
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 is video pricing calculated?
Video processing uses either token-based billing (263 tokens per second) or duration-based billing for video generation models like Veo ($0.15-0.75 per second depending on resolution).
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 44+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), and provides optimization recommendations.