AI Agentic Coding: Full Repo Refactor Cost 2026

claude-sonnet-4.5 vs gpt-5
Complete Comparison: 650,000 input tokens × 200,000 output tokens
Comparison Mode (Custom field comparison)
⚡ 60% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 60% Cached.

⚡ Caching Optimized (up to 90% savings)
Comparison Criteria claude-sonnet-4.5
Anthropic
gpt-5
OpenAI
Input Parameters Applied (60% cached)
Input Tokens 650,000 650,000
Output Tokens 200,000 200,000
Calculation Results
Input Cost $3.250000 Worst $1.137500 (rounded ~ 1.14) Best
Output Cost $5.000000 Worst $2.800000 Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $8.300000 Most Expensive $3.987500 (rounded ~ 3.99) Best Value
Processing Time 28 minutes, 54.00 seconds Fastest 32 minutes, 6.00 seconds Slowest
Tokens per Second 500 Fastest 450 Slowest
Time to First Token 200ms 200ms
Cost per 1K tokens $0.009765 Worst $0.003969 (rounded ~ 0.00) Best
Tokens per Dollar 102,410 Worst Value 251,983 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
$1.750000 Best
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $25.000000 Worst
Optimizations: No optimizations applied
$14.000000 Best
Optimizations: No optimizations applied
Capabilities
Caching Support ✗ Not Supported ✓ Supported
Batch API Support ✗ Not Supported Available
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

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
$8.300000Total Cost
$3.250000Input Cost
$5.000000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
850,000Total Tokens
$0.009765Cost per 1K
102,410Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
28m 54sProcessing Time
500Tokens/Second
200msTime to First Token
490Effective Speed

Model Comparison

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Model Information

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🔄 Advanced Options

⚡ Optimization
60%
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

$8.300000
Total Cost
⚡ 60% Cached 🔧 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) $8.300000 Input: $3.250000
Output: $5.000000
Optimized Cost $8.300000 Input: $3.250000
Output: $5.000000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 650,000 input tokens and 200,000 output tokens:

  • Input Cost: $3.250000
  • Output Cost: $5.000000
  • Service Fees: $0.050000
  • Total Cost: $8.300000
  • Cost per 1K tokens: $0.009765
  • Tokens per dollar: 102,410 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: 28 minutes, 54.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 490 tokens/second (temperature-adjusted)

Best Use Cases

Software EngineeringLegacy MigrationRefactoringTechnical Debt

gpt-5 OpenAI

$3.987500 (rounded ~ 3.99)
Total Cost
⚠️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 400,000 tokens.
⚡ 60% Cached 🔧 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) $3.987500 (rounded ~ 3.99) Input: $1.137500 (rounded ~ 1.14)
Output: $2.800000
Optimized Cost $3.987500 (rounded ~ 3.99) Input: $1.137500 (rounded ~ 1.14)
Output: $2.800000
Unit: $0.000000
Fees: $0.050000
Total Savings $0.614250 (rounded ~ 0.61) 15.4% discount

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 650,000 input tokens and 200,000 output tokens:

  • Input Cost: $1.137500 (rounded ~ 1.14)
  • Output Cost: $2.800000
  • Service Fees: $0.050000
  • Total Cost: $3.987500 (rounded ~ 3.99)
  • Cost per 1K tokens: $0.003969 (rounded ~ 0.00)
  • Tokens per dollar: 251,983 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: 32 minutes, 6.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 441 tokens/second (temperature-adjusted)

Best Use Cases

Software EngineeringLegacy MigrationRefactoringTechnical Debt

Automated Software Engineering Economics

Calculating the complete unit economics of using advanced autonomous coding agents for full-scale repository refactoring, technical debt reduction, and legacy system modernization in 2026 enterprise environments. This comprehensive analysis factors in multi-step reasoning loops, tool usage overhead, and cache optimization for repetitive code patterns.

Agent Workflow Setup & Cost Drivers

  • Codebase Size: 150,000 lines (~600K tokens including comments/documentation)
  • Planning Phase: 50,000 reasoning tokens for architecture analysis
  • Implementation Phase: 200,000 output tokens for actual code generation
  • Testing/Debug Loops: 5 iterations with cumulative token costs
  • Cache Efficiency: 60% via local context of repeated code patterns
  • Tool Usage: 10% cost multiplier for function calling and API integrations
  • Temperature Setting: 0.2 for deterministic, reproducible refactoring

Developer Productivity & ROI Analysis

Legacy migration projects, architectural refactoring initiatives, automated documentation generation, unit test suite creation at scale. This calculator helps engineering managers budget for AI-assisted code modernization, comparing Claude Sonnet’s superior reasoning capabilities against specialized coding models. The analysis includes batch API optimization for overnight processing and fine-tuning considerations for proprietary codebases.

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 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.
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.