GPT-5 vs Claude Opus 4.5 API Pricing Calculator

gpt-5 vs claude-opus-4.5
Complete Comparison: 50,000 input tokens × 25,000 output tokens
Comparison Mode (Custom field comparison)

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

Comparison Criteria gpt-5
OpenAI
claude-opus-4.5
Anthropic
Input Parameters Applied
Input Tokens 50,000 50,000
Output Tokens 25,000 25,000
Calculation Results
Input Cost $0.087500 (rounded ~ 0.09) Best $0.250000 Worst
Output Cost $0.350000 Best $0.625000 (rounded ~ 0.63) Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.437500 (rounded ~ 0.44) Best Value $0.875000 (rounded ~ 0.88) Most Expensive
Processing Time 2 minutes, 58.00 seconds Slowest 2 minutes, 40.00 seconds Fastest
Tokens per Second 450 Slowest 500 Fastest
Time to First Token 200ms 200ms
Cost per 1K tokens $0.005833 (rounded ~ 0.01) Best $0.011667 (rounded ~ 0.01) Worst
Tokens per Dollar 171,429 Best Value 85,714 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.750000 Best $5.000000 Worst
Output Cost / 1M (Base) $14.000000 Best $25.000000 Worst
Input Cost / 1M (Optimized) $1.750000 Best
Optimizations: No optimizations applied
$5.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $14.000000 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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All other parameters will be preserved from the current comparison.

Select AI Model

Gpt 5
OpenAIMax Context: 400,000 tokens
Input: $1.750000 / 1M
Output: $14.000000 / 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
$0.437500Total Cost
$0.087500Input Cost
$0.350000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
75,000Total Tokens
$0.005833Cost per 1K
171,429Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
2m 58sProcessing Time
450Tokens/Second
200msTime to First Token
421Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 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

$0.437500 (rounded ~ 0.44)
Total Cost
👁️
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) $0.437500 (rounded ~ 0.44) Input: $0.087500 (rounded ~ 0.09)
Output: $0.350000
Optimized Cost $0.437500 (rounded ~ 0.44) Input: $0.087500 (rounded ~ 0.09)
Output: $0.350000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 50,000 input tokens and 25,000 output tokens:

  • Input Cost: $0.087500 (rounded ~ 0.09)
  • Output Cost: $0.350000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $0.437500 (rounded ~ 0.44)
  • Cost per 1K tokens: $0.005833 (rounded ~ 0.01)
  • Tokens per dollar: 171,429 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, 58.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 421 tokens/second

Best Use Cases

Enterprise AIComplex reasoningResearch analysis

claude-opus-4.5 Anthropic 1000000

$0.875000 (rounded ~ 0.88)
Total Cost
👁️
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) $0.875000 (rounded ~ 0.88) Input: $0.250000
Output: $0.625000 (rounded ~ 0.63)
Optimized Cost $0.875000 (rounded ~ 0.88) Input: $0.250000
Output: $0.625000 (rounded ~ 0.63)
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 50,000 input tokens and 25,000 output tokens:

  • Input Cost: $0.250000
  • Output Cost: $0.625000 (rounded ~ 0.63)
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $0.875000 (rounded ~ 0.88)
  • Cost per 1K tokens: $0.011667 (rounded ~ 0.01)
  • Tokens per dollar: 85,714 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: 2 minutes, 40.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 467 tokens/second

Best Use Cases

Enterprise AIComplex reasoningResearch analysis

GPT-5 vs Claude Opus 4.5: Complete API Cost Analysis

Compare OpenAI’s GPT-5 with Anthropic’s Claude Opus 4.5 for enterprise AI applications. This detailed analysis includes multimodal capabilities, reasoning costs, and optimization strategies.

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 38 AI models. It calculates token-based pricing, analyzes multimodal processing, and provides optimization recommendations.