Cost per 10,000 Tokens: Comparing AI Coding Models for IDE Integration

Claude Sonnet 4.6 vs GPT-5.3 Codex Spark
Complete Comparison: 10,000 input tokens × 500 output tokens
Comparison Mode
⚡ 30% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 30% Cached.

⚡ Caching Optimized (up to 90% savings)
Comparison Criteria Claude Sonnet 4.6
Anthropic
GPT-5.3 Codex Spark
OpenAI
Calculation Results (Current Inputs) (30% cached)
Input Tokens 10,000 10,000
Output Tokens 500 500
Cost Breakdown
Input Cost $0.030000Worst $0.017500 (rounded ~ $0.02)Best
Output Cost $0.007500 (rounded ~ $0.01)Worst $0.007000 (rounded ~ $0.01)Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.029400 Most Expensive $0.019775 Best Value
Processing Time 23.98 seconds Slowest 10.89 seconds Fastest
Tokens per Second 450Slowest 1,000Fastest
Time to First Token 200ms Worst 100ms Best
Cost per 1K tokens $0.002800Worst $0.001883Best
Tokens per Dollar 357,143Worst Value 530,973Best Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $3.000000Worst $1.750000Best
Output Cost / 1M (Base) $15.000000Worst $14.000000Best
Input Cost / 1M (Optimized) $3.000000Worst
Optimizations: No optimizations applied
$1.750000Best
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $15.000000Worst
Optimizations: No optimizations applied
$14.000000Best
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✓ Supported ✓ Supported
Caching Support
30
✓ Supported ✓ Supported
Batch API Support ✓ Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
Scroll horizontally to see all data

🔄 Compare Different AI Models

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All other parameters will be preserved from the current comparison.

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Select AI Model

Claude Sonnet 4.6
AnthropicMax Context: 1,000,000 tokens
$3 / $15 per 1M tokens
Use Batch API (50% discount)
30%
Provider-specific multipliers applied after all calculations
Enable for cache discounts
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.

Calculate Token Costs

$0.021000 Input Cost
$0.007500 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
10,500Total Tokens
$0.002800Cost per 1K
357,143Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

23.98s Processing Time
450 Tokens/Second
200ms Time to First Token
441 Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 Advanced Options

⚡ Optimization
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data
First 50 hours free, $0.05/hour after

🧠 Reasoning & Thinking
Manual thinking tokens (billed at output rate)

🔧 Special Modes
Enable 6.0x Fast Mode multiplier

📚 Research & Citations
Enable $1.00/$4.00 rates + $10.00/1k search
Enable research tier pricing
Fee per source cited

🎤 Realtime Audio & Video
Session length for billing
📊 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 4.6 Anthropic 1000000

$0.029400
Total Cost
⚡ 30% 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 (from Plugin)

Base Cost (No Optimizations) $0.037500 (rounded ~ $0.04) Input: $0.030000
Output: $0.007500 (rounded ~ $0.01)
Optimized Cost $0.029400 Input: $0.030000
Output: $0.007500 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.008100 (rounded ~ $0.01) 21.6% discount

Detailed Cost Analysis (from Plugin)

For 10,000 input tokens and 500 output tokens:

  • Input Cost: $0.030000
  • Output Cost: $0.007500 (rounded ~ $0.01)
  • Total Cost: $0.029400
  • Cost per 1K tokens: $0.002800
  • Tokens per dollar: 357,143 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

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

  • Processing Time: 23.98 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 441 tokens/second (temperature-adjusted)

Best Use Cases

Best for real-time IDE extensions requiring a balance between deep architectural understanding and low-latency autocomplete suggestions.

Want this applied to YOUR actual stack?

This calculator shows the math for Claude Sonnet 4.6. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.

Get my instant AI audit — $39 →

GPT-5.3 Codex Spark OpenAI

$0.019775
Total Cost
⚡ 30% 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 (from Plugin)

Base Cost (No Optimizations) $0.024500 (rounded ~ $0.02) Input: $0.017500 (rounded ~ $0.02)
Output: $0.007000 (rounded ~ $0.01)
Optimized Cost $0.019775 Input: $0.017500 (rounded ~ $0.02)
Output: $0.007000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.004725 19.3% discount

Detailed Cost Analysis (from Plugin)

For 10,000 input tokens and 500 output tokens:

  • Input Cost: $0.017500 (rounded ~ $0.02)
  • Output Cost: $0.007000 (rounded ~ $0.01)
  • Total Cost: $0.019775
  • Cost per 1K tokens: $0.001883
  • Tokens per dollar: 530,973 tokens
  • Context Window: 200000 tokens

Speed & Performance Analysis

With a processing speed of 1,000 tokens per second and 100ms time to first token:

  • Processing Time: 10.89 seconds
  • Latency: 100 milliseconds to first token
  • Base Throughput: 1,000 tokens/second
  • Effective Throughput: 980 tokens/second (temperature-adjusted)

Best Use Cases

Best for real-time IDE extensions requiring a balance between deep architectural understanding and low-latency autocomplete suggestions.

Want this applied to YOUR actual stack?

This calculator shows the math for GPT-5.3 Codex Spark. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.

Get my instant AI audit — $39 →

✨ Market Recommendations AI Model Registry

← Back to Claude Sonnet 4.6
📋 Active Input Parameters
Input Tokens: 10,000
Output Tokens: 500
Cached Tokens: 30%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Claude Sonnet 4.6 vs GPT-5.3 Codex Spark
🏆 Mistral Small 3
Mistral AI
$0.000880 Best Value ↓ 97% cheaper ↓ 95.5% cheaper
🥈 Grok Code Fast 1
xAI
$0.002210 ↓ 92.5% cheaper ↓ 88.8% cheaper
🥉 Gemini 3.1 Flash Lite
Google
$0.002575 ↓ 91.2% cheaper ↓ 87% cheaper
#4 Gemini 2.5 Flash
Google
$0.003440 ↓ 88.3% cheaper ↓ 82.6% cheaper
#5 Mistral Large 3
Mistral AI
$0.004400 ↓ 85% cheaper ↓ 77.7% cheaper
#6 Gemini 3.1 Flash
Google
$0.005150 (rounded ~ $0.01) ↓ 82.5% cheaper ↓ 74% cheaper
#7 Kimi K2.5
Moonshot AI
$0.006006 (rounded ~ $0.01) ↓ 79.6% cheaper ↓ 69.6% cheaper
#8 GPT-5.4 mini
OpenAI
$0.007725 (rounded ~ $0.01) ↓ 73.7% cheaper ↓ 60.9% cheaper
#9 Kimi K2.6
Moonshot AI
$0.009135 ↓ 68.9% cheaper ↓ 53.8% cheaper
#10 o4-mini Deep Research
OpenAI
$0.009300 ↓ 68.4% cheaper ↓ 53% cheaper
#11 Claude Haiku 4.5
Anthropic
$0.009800 ↓ 66.7% cheaper ↓ 50.4% cheaper
#12 o4-mini
OpenAI
$0.010230 ↓ 65.2% cheaper ↓ 48.3% cheaper
#13 Grok 4.3
xAI
$0.010375 ↓ 64.7% cheaper ↓ 47.5% cheaper
#14 Gemini 2.5 Pro
Google
$0.014125 (rounded ~ $0.01) ↓ 52% cheaper ↓ 28.6% cheaper
#15 Gemini 3.5 Flash
Google
$0.015450 (rounded ~ $0.02) ↓ 47.4% cheaper ↓ 21.9% cheaper
#16 Grok 4.20 Beta
xAI
$0.017600 (rounded ~ $0.02) ↓ 40.1% cheaper ↓ 11% cheaper
#17 GPT-5.3 Codex Spark
OpenAI
$0.019775 ↓ 32.7% cheaper Same price
#18 GPT-5.3 Instant
OpenAI
$0.019775 ↓ 32.7% cheaper Same price
#19 Gemini 3.1 Pro
Google
$0.020600 ↓ 29.9% cheaper ↑ 4.2% more
#20 GPT-5.4
OpenAI
$0.025750 (rounded ~ $0.03) ↓ 12.4% cheaper ↑ 30.2% more
#21 GPT-5.4 Thinking
OpenAI
$0.025750 (rounded ~ $0.03) ↓ 12.4% cheaper ↑ 30.2% more
#22 Claude Opus 4.7
Anthropic
$0.049000 (rounded ~ $0.05) ↑ 66.7% more ↑ 147.8% more
#23 Claude Opus 4.8
Anthropic
$0.049000 (rounded ~ $0.05) ↑ 66.7% more ↑ 147.8% more
#24 Claude Opus 4.6
Anthropic
$0.049000 (rounded ~ $0.05) ↑ 66.7% more ↑ 147.8% more
#25 GPT-5.5
OpenAI
$0.051500 (rounded ~ $0.05) ↑ 75.2% more ↑ 160.4% more
#26 GPT-5.5 Instant
OpenAI
$0.051500 (rounded ~ $0.05) ↑ 75.2% more ↑ 160.4% more
#27 o3 Deep Research
OpenAI
$0.093000 (rounded ~ $0.09) ↑ 216.3% more ↑ 370.3% more
#28 o3 Pro
OpenAI
$0.186000 (rounded ~ $0.19) ↑ 532.7% more ↑ 840.6% more
#29 GPT-5.2 Pro
OpenAI
$0.237300 (rounded ~ $0.24) ↑ 707.1% more ↑ 1100% more
#30 GPT-5.2 Pro
OpenAI
$0.237300 (rounded ~ $0.24) ↑ 707.1% more ↑ 1100% more
🏆

Mistral Small 3
Mistral AI

$0.000880
vs Claude Sonnet 4.6: ↓ 97%
vs GPT-5.3 Codex Spark: ↓ 95.5%
🥈

Grok Code Fast 1
xAI

$0.002210
vs Claude Sonnet 4.6: ↓ 92.5%
vs GPT-5.3 Codex Spark: ↓ 88.8%
🥉

Gemini 3.1 Flash Lite
Google

$0.002575
vs Claude Sonnet 4.6: ↓ 91.2%
vs GPT-5.3 Codex Spark: ↓ 87%
#4

Gemini 2.5 Flash
Google

$0.003440
vs Claude Sonnet 4.6: ↓ 88.3%
vs GPT-5.3 Codex Spark: ↓ 82.6%
#5

Mistral Large 3
Mistral AI

$0.004400
vs Claude Sonnet 4.6: ↓ 85%
vs GPT-5.3 Codex Spark: ↓ 77.7%
#6

Gemini 3.1 Flash
Google

$0.005150 (rounded ~ $0.01)
vs Claude Sonnet 4.6: ↓ 82.5%
vs GPT-5.3 Codex Spark: ↓ 74%
#7

Kimi K2.5
Moonshot AI

$0.006006 (rounded ~ $0.01)
vs Claude Sonnet 4.6: ↓ 79.6%
vs GPT-5.3 Codex Spark: ↓ 69.6%
#8

GPT-5.4 mini
OpenAI

$0.007725 (rounded ~ $0.01)
vs Claude Sonnet 4.6: ↓ 73.7%
vs GPT-5.3 Codex Spark: ↓ 60.9%
#9

Kimi K2.6
Moonshot AI

$0.009135
vs Claude Sonnet 4.6: ↓ 68.9%
vs GPT-5.3 Codex Spark: ↓ 53.8%
#10

o4-mini Deep Research
OpenAI

$0.009300
vs Claude Sonnet 4.6: ↓ 68.4%
vs GPT-5.3 Codex Spark: ↓ 53%
#11

Claude Haiku 4.5
Anthropic

$0.009800
vs Claude Sonnet 4.6: ↓ 66.7%
vs GPT-5.3 Codex Spark: ↓ 50.4%
#12

o4-mini
OpenAI

$0.010230
vs Claude Sonnet 4.6: ↓ 65.2%
vs GPT-5.3 Codex Spark: ↓ 48.3%
#13

Grok 4.3
xAI

$0.010375
vs Claude Sonnet 4.6: ↓ 64.7%
vs GPT-5.3 Codex Spark: ↓ 47.5%
#14

Gemini 2.5 Pro
Google

$0.014125 (rounded ~ $0.01)
vs Claude Sonnet 4.6: ↓ 52%
vs GPT-5.3 Codex Spark: ↓ 28.6%
#15

Gemini 3.5 Flash
Google

$0.015450 (rounded ~ $0.02)
vs Claude Sonnet 4.6: ↓ 47.4%
vs GPT-5.3 Codex Spark: ↓ 21.9%
#16

Grok 4.20 Beta
xAI

$0.017600 (rounded ~ $0.02)
vs Claude Sonnet 4.6: ↓ 40.1%
vs GPT-5.3 Codex Spark: ↓ 11%
#17

GPT-5.3 Codex Spark
OpenAI

$0.019775
vs Claude Sonnet 4.6: ↓ 32.7%
vs GPT-5.3 Codex Spark: Same
#18

GPT-5.3 Instant
OpenAI

$0.019775
vs Claude Sonnet 4.6: ↓ 32.7%
vs GPT-5.3 Codex Spark: Same
#19

Gemini 3.1 Pro
Google

$0.020600
vs Claude Sonnet 4.6: ↓ 29.9%
vs GPT-5.3 Codex Spark: ↑ 4.2%
#20

GPT-5.4
OpenAI

$0.025750 (rounded ~ $0.03)
vs Claude Sonnet 4.6: ↓ 12.4%
vs GPT-5.3 Codex Spark: ↑ 30.2%
#21

GPT-5.4 Thinking
OpenAI

$0.025750 (rounded ~ $0.03)
vs Claude Sonnet 4.6: ↓ 12.4%
vs GPT-5.3 Codex Spark: ↑ 30.2%
#22

Claude Opus 4.7
Anthropic

$0.049000 (rounded ~ $0.05)
vs Claude Sonnet 4.6: ↑ 66.7%
vs GPT-5.3 Codex Spark: ↑ 147.8%
#23

Claude Opus 4.8
Anthropic

$0.049000 (rounded ~ $0.05)
vs Claude Sonnet 4.6: ↑ 66.7%
vs GPT-5.3 Codex Spark: ↑ 147.8%
#24

Claude Opus 4.6
Anthropic

$0.049000 (rounded ~ $0.05)
vs Claude Sonnet 4.6: ↑ 66.7%
vs GPT-5.3 Codex Spark: ↑ 147.8%
#25

GPT-5.5
OpenAI

$0.051500 (rounded ~ $0.05)
vs Claude Sonnet 4.6: ↑ 75.2%
vs GPT-5.3 Codex Spark: ↑ 160.4%
#26

GPT-5.5 Instant
OpenAI

$0.051500 (rounded ~ $0.05)
vs Claude Sonnet 4.6: ↑ 75.2%
vs GPT-5.3 Codex Spark: ↑ 160.4%
#27

o3 Deep Research
OpenAI

$0.093000 (rounded ~ $0.09)
vs Claude Sonnet 4.6: ↑ 216.3%
vs GPT-5.3 Codex Spark: ↑ 370.3%
#28

o3 Pro
OpenAI

$0.186000 (rounded ~ $0.19)
vs Claude Sonnet 4.6: ↑ 532.7%
vs GPT-5.3 Codex Spark: ↑ 840.6%
#29

GPT-5.2 Pro
OpenAI

$0.237300 (rounded ~ $0.24)
vs Claude Sonnet 4.6: ↑ 707.1%
vs GPT-5.3 Codex Spark: ↑ 1100%
#30

GPT-5.2 Pro
OpenAI

$0.237300 (rounded ~ $0.24)
vs Claude Sonnet 4.6: ↑ 707.1%
vs GPT-5.3 Codex Spark: ↑ 1100%
✨ How recommendations work (v8.6.0): We scan all active models in the registry and only include those that support ALL your current inputs. For token-based models, we check if they can handle your token counts. For special pricing models (OCR, video, audio), we verify they have the correct pricing structure. Features marked requested were in your inputs but not supported by that model. Now using official provider pricing without reseller markups.

Optimizing IDE Performance for E-commerce Development

For e-commerce platform owners, integrating AI-driven inline code suggestions is no longer a luxury but a requirement for maintaining complex, multilingual product catalogs and backend logic. When evaluating 10,000-token context windows for each suggestion, the choice between flagship models hinges on how they handle surrounding file metadata and specific framework syntax. This comparison focuses on the qualitative trade-offs between two industry leaders in the software development domain.

Claude Sonnet 4.6 is frequently lauded for its exceptional ability to maintain architectural consistency across large snippets. In an IDE setting, this translates to suggestions that are contextually aware of the broader project structure rather than just the immediate line of code. Its strength lies in understanding developer intent across complex multi-file dependencies, which significantly reduces the need for manual refactoring. However, the depth of its reasoning can sometimes introduce higher latency compared to highly specialized coding variants.

GPT-5.3 Codex Spark represents a refined approach to real-time developer assistance, optimized specifically for the autocomplete experience. It excels in scenarios where speed and fluidity are the primary metrics. By prioritizing lower time-to-first-token, it provides a more seamless experience for engineers working on high-speed UI iterations or routine data transformations. While it may occasionally lack the structural foresight found in the Claude family, its responsiveness makes it a favorite for teams focused on rapid prototyping. Selecting the right model depends on whether your engineering team prioritizes the intellectual depth of suggestions or the immediate flow of the human-in-the-loop experience.

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. Note: Reseller markups and dedicated instance multipliers have been removed to reflect official provider 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.
How do Market Recommendations work (v8.6.0)?
Our recommendation engine scans the entire model registry and only includes models that support ALL your current input parameters (tokens, images, video, audio, OCR, tools, batch API, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options that can handle your complete workflow. Special pricing models (OCR, video, audio, image generation) are properly handled and only appear when their specific input types are requested. v8.6.0 removes reseller markups (20% buffer) and dedicated instance multipliers to reflect official provider 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 50+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), provides optimization recommendations, and now offers intelligent market matching to find the best alternatives for your specific needs.