Long Context AI Cost: Gemini 3 Pro 1M Context vs Claude 4.5 200K

gemini-3-1-pro vs claude-opus-4.5
Complete Comparison: 500,000 input tokens × 100,000 output tokens
Comparison Mode (Custom field comparison)

Complete comparison of pricing, performance, and capabilities for 2 leading AI models .

Comparison Criteria gemini-3-1-pro
Google
claude-opus-4.5
Anthropic
Input Parameters Applied
Input Tokens 500,000 500,000
Output Tokens 100,000 100,000
Calculation Results
Input Cost $0.500000 Best $2.500000 Worst
Output Cost $0.500000 Best $2.500000 Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $1.050000 Best Value $5.050000 Most Expensive
Processing Time 25 minutes, 45.00 seconds Slowest 20 minutes, 36.00 seconds Fastest
Tokens per Second 400 Slowest 500 Fastest
Time to First Token 220ms Worst 200ms Best
Cost per 1K tokens $0.001750 (rounded ~ 0.00) Best $0.008417 (rounded ~ 0.01) Worst
Tokens per Dollar 571,429 Best Value 118,812 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.000000 Best $5.000000 Worst
Output Cost / 1M (Base) $5.000000 Best $25.000000 Worst
Input Cost / 1M (Optimized) $1.000000 Best
Optimizations: No optimizations applied
$5.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $5.000000 Best
Optimizations: No optimizations applied
$25.000000 Worst
Optimizations: No optimizations applied
Capabilities
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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All other parameters will be preserved from the current comparison.

Select AI Model

Gemini 3.1 Pro
GoogleMax Context: 2,000,000 tokens
Input: $1.000000 / 1M
Output: $5.000000 / 1M

Calculate Token Costs

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▼
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
$1.050000Total Cost
$0.500000Input Cost
$0.500000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
600,000Total Tokens
$0.001750Cost per 1K
571,429Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
25m 45sProcessing Time
400Tokens/Second
220msTime to First Token
388Effective 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.

gemini-3-1-pro Google 2000000

$1.050000
Total Cost
🔧 Tools
👁️
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

Base Cost (No Optimizations) $1.050000 Input: $0.500000
Output: $0.500000
Optimized Cost $1.050000 Input: $0.500000
Output: $0.500000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 500,000 input tokens and 100,000 output tokens:

  • Input Cost: $0.500000
  • Output Cost: $0.500000
  • Service Fees: $0.050000
  • Total Cost: $1.050000
  • Cost per 1K tokens: $0.001750 (rounded ~ 0.00)
  • Tokens per dollar: 571,429 tokens
  • Context Window: 2000000 tokens

Speed & Performance Analysis

With a processing speed of 400 tokens per second and 220ms time to first token:

  • Processing Time: 25 minutes, 45.00 seconds
  • Latency: 220 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 388 tokens/second (temperature-adjusted)

Best Use Cases

Document analysisResearchLong context

claude-opus-4.5 Anthropic 1000000

$5.050000
Total Cost
🔧 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) $5.050000 Input: $2.500000
Output: $2.500000
Optimized Cost $5.050000 Input: $2.500000
Output: $2.500000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 500,000 input tokens and 100,000 output tokens:

  • Input Cost: $2.500000
  • Output Cost: $2.500000
  • Service Fees: $0.050000
  • Total Cost: $5.050000
  • Cost per 1K tokens: $0.008417 (rounded ~ 0.01)
  • Tokens per dollar: 118,812 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

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

  • Processing Time: 20 minutes, 36.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 485 tokens/second (temperature-adjusted)

Best Use Cases

Document analysisResearchLong context

Extended Context Economics

Comparing models with massive context windows for document analysis and research applications.

Context Analysis

  • Gemini 3 Pro: 1,000,000 token context
  • Claude 4.5: 200,000 token context
  • Gemini tiered pricing: $2→$4/1M after 200K
  • Claude flat pricing: $5/1M throughout

Document Processing

Gemini for books/long reports. Claude for standard documents.

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.
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.