Claude 4.5 Sonnet vs GPT-5.2: The Coding Workhorses

claude-sonnet-4.5 vs gpt-5.2
Complete Comparison: 80,000 input tokens × 10,000 output tokens
Comparison Mode (Custom field comparison)

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

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria claude-sonnet-4.5
Anthropic
gpt-5.2
OpenAI
Input Parameters Applied (90% cached)
Input Tokens 80,000 80,000
Output Tokens 10,000 10,000
Calculation Results
Input Cost $0.400000 Worst $0.140000 Best
Output Cost $0.250000 Worst $0.140000 Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $0.700000 Most Expensive $0.330000 Best Value
Processing Time 3 minutes, 3.00 seconds Fastest 3 minutes, 24.00 seconds Slowest
Tokens per Second 500 Fastest 450 Slowest
Time to First Token 200ms 200ms
Cost per 1K tokens $0.007778 (rounded ~ 0.01) Worst $0.001481 (rounded ~ 0.00) Best
Tokens per Dollar 128,571 Worst Value 675,169 Best Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $5.000000 Worst $1.750000 Best
Output Cost / 1M (Base) $25.000000 Worst $14.000000 Best
Input Cost / 1M (Optimized) $5.000000 Worst
Optimizations: No optimizations applied
$0.875000 (rounded ~ 0.88) Best
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) $25.000000 Worst
Optimizations: No optimizations applied
$7.000000 Best
Optimizations: 50.0% batch
Capabilities
Caching Support ✗ Not Supported ✓ Supported
Batch API Support ✗ Not Supported ✓ Enabled
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
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🔄 Compare Different AI Models

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All other parameters will be preserved from the current comparison.

Select AI Model

Claude Sonnet 4 5
AnthropicMax Context: 1,000,000 tokens
Input: $5.000000 / 1M
Output: $25.000000 / 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
$0.700000Total Cost
$0.400000Input Cost
$0.250000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
90,000Total Tokens
$0.007778Cost per 1K
128,571Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
3m 3sProcessing Time
500Tokens/Second
200msTime to First Token
490Effective Speed

Model Comparison

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Model Information

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🔄 Advanced Options

⚡ Optimization
90%
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.

claude-sonnet-4.5 Anthropic 1000000

$0.700000
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) $0.700000 Input: $0.400000
Output: $0.250000
Optimized Cost $0.700000 Input: $0.400000
Output: $0.250000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 80,000 input tokens and 10,000 output tokens:

  • Input Cost: $0.400000
  • Output Cost: $0.250000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $0.700000
  • Cost per 1K tokens: $0.007778 (rounded ~ 0.01)
  • Tokens per dollar: 128,571 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: 3 minutes, 3.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 490 tokens/second

Best Use Cases

Software EngineeringSQL GenerationDocumentation

gpt-5.2 OpenAI

$0.330000
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) $0.330000 Input: $0.140000
Output: $0.140000
Optimized Cost $0.330000 Input: $0.140000
Output: $0.140000
Unit: $0.000000
Fees: $0.050000
Total Savings $0.196700 (rounded ~ 0.20) 59.6% discount

Advanced Cost Breakdown

📊 Batch API
50.0% off
Asynchronous processing
💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 80,000 input tokens and 10,000 output tokens:

  • Input Cost: $0.140000
  • Output Cost: $0.140000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $0.330000
  • Cost per 1K tokens: $0.001481 (rounded ~ 0.00)
  • Tokens per dollar: 675,169 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: 3 minutes, 24.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 441 tokens/second

Best Use Cases

Software EngineeringSQL GenerationDocumentation

Developer ROI Benchmarks

For mid-tier pricing, these two models handle 90% of production coding tasks. We compare the ‘Cache Hit’ discounts of Anthropic vs. the ‘Batch API’ savings of OpenAI to find the cheapest way to run an autonomous DevOps pipeline.

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.