DeepSeek V4 vs Claude Sonnet 4.6: Coding ROI

DeepSeek V4 (Engram) vs Claude Sonnet 4.6
Complete Comparison: 500,000 input tokens × 100,000 output tokens
Comparison Mode
⚡ 90% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 90% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria DeepSeek V4 (Engram)
DeepSeek
Claude Sonnet 4.6
Anthropic
Calculation Results (Current Inputs) (90% cached)
Input Tokens N/A (Special Pricing) 500,000
Output Tokens N/A (Special Pricing) 100,000
Cost Breakdown
Input Cost N/A (Special Pricing) $0.375000 (rounded ~ $0.38)
Output Cost N/A (Special Pricing) $0.375000 (rounded ~ $0.38)
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.128325 (rounded ~ $0.13) Best Value $0.446250 (rounded ~ $0.45) Most Expensive
Processing Time 34 minutes, 40.18 seconds Slowest 23 minutes, 6.85 seconds Fastest
Tokens per Second N/A (Special Pricing) 450
Time to First Token 180ms Best 200ms Worst
Cost per 1K tokens N/A (Special Pricing) $0.000744
Tokens per Dollar N/A (Special Pricing) 1,344,538
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) N/A (Special Pricing) $0.750000
Output Cost / 1M (Base) N/A (Special Pricing) $3.750000
Input Cost / 1M (Optimized) N/A (Special Pricing) $0.375000 (rounded ~ $0.38)
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) N/A (Special Pricing) $1.875000 (rounded ~ $1.88)
Optimizations: 50.0% batch
Capabilities & Advanced Features
Images Support ✗ Not Supported ✓ Supported
Caching Support
90
✓ Supported ✓ Supported
Batch API Support ✗ Not Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
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Select AI Model

Deepseek V4
DeepSeekMax Context: 1,000,000 tokens
$0.435 / $0.87 per 1M tokens
▼
▼
Use Batch API (50% discount)
90%
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

$0.128325 Total Cost
$0.021750 Input Cost
$0.087000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
600,000Total Tokens
$0.000214Cost per 1K
4,675,628Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

34m 40s Processing Time
300 Tokens/Second
180ms Time to First Token
288 Effective Speed

Model Comparison

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Model Information

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🔄 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.

DeepSeek V4 (Engram) DeepSeek 1000000

$0.128325 (rounded ~ $0.13)
Total Cost
⚡ 90% Cached 📊 Batch API 🔧 Tools
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✗ Not Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.304500 (rounded ~ $0.30) Input: $0.217500 (rounded ~ $0.22)
Output: $0.087000 (rounded ~ $0.09)
Optimized Cost $0.128325 (rounded ~ $0.13) Input: $0.217500 (rounded ~ $0.22)
Output: $0.087000 (rounded ~ $0.09)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.176175 (rounded ~ $0.18) 57.9% discount

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.217500 (rounded ~ $0.22)
  • Output Cost: $0.087000 (rounded ~ $0.09)
  • Total Cost: $0.128325 (rounded ~ $0.13)
  • Cost per 1K tokens: $0.000214
  • Tokens per dollar: 4,675,628 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 300 tokens per second and 180ms time to first token:

  • Processing Time: 34 minutes, 40.18 seconds
  • Latency: 180 milliseconds to first token
  • Base Throughput: 300 tokens/second
  • Effective Throughput: 288 tokens/second (temperature-adjusted)

Best Use Cases

Autonomous RefactoringSystem Design

Want this applied to YOUR actual stack?

This calculator shows the math for DeepSeek V4 (Engram). Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

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Claude Sonnet 4.6 Anthropic 1000000

$0.446250 (rounded ~ $0.45)
Total Cost
⚡ 90% Cached 📊 Batch API 🔧 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) $0.750000 Input: $0.375000 (rounded ~ $0.38)
Output: $0.375000 (rounded ~ $0.38)
Optimized Cost $0.446250 (rounded ~ $0.45) Input: $0.375000 (rounded ~ $0.38)
Output: $0.375000 (rounded ~ $0.38)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.303750 (rounded ~ $0.30) 40.5% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.375000 (rounded ~ $0.38)
  • Output Cost: $0.375000 (rounded ~ $0.38)
  • Total Cost: $0.446250 (rounded ~ $0.45)
  • Cost per 1K tokens: $0.000744
  • Tokens per dollar: 1,344,538 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 minutes, 6.85 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 433 tokens/second (temperature-adjusted)

Best Use Cases

Autonomous RefactoringSystem Design

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 →

✨ Market Recommendations AI Model Registry

← Back to DeepSeek V4 (Engram)
📋 Active Input Parameters
Input Tokens: 500,000
Output Tokens: 100,000
Batch API: Enabled (50% discount)
Cached Tokens: 90%
Tools: Enabled
Rank AI Model & Provider Total Cost vs DeepSeek V4 (Engram) vs Claude Sonnet 4.6
🏆 Gemini 3.1 Flash Lite
Google
 $0.043438 (rounded ~ $0.04) Best Value ↓ 66.2% cheaper ↓ 90.3% cheaper
🥈 Gemini 2.5 Flash
Google
 $0.069625 ↓ 45.7% cheaper ↓ 84.4% cheaper
🥉 Grok 4.3
xAI
 $0.092188 (rounded ~ $0.09) ↓ 28.2% cheaper ↓ 79.3% cheaper
#4 Grok 4.20 Beta
xAI
 $0.197500 (rounded ~ $0.20) ↑ 53.9% more ↓ 55.7% cheaper
#5 Gemini 3.5 Flash
Google
 $0.260625 ↑ 103.1% more ↓ 41.6% cheaper
#6 Gemini 3.1 Flash
Google
 $0.347500 (rounded ~ $0.35) ↑ 170.8% more ↓ 22.1% cheaper
#7 Claude Sonnet 4.6
Anthropic
 $0.446250 (rounded ~ $0.45) ↑ 247.7% more Same price
#8 Claude Opus 4.7
Anthropic
 $0.743750 (rounded ~ $0.74) ↑ 479.6% more ↑ 66.7% more
#9 Claude Opus 4.8
Anthropic
 $0.743750 (rounded ~ $0.74) ↑ 479.6% more ↑ 66.7% more
#10 Claude Opus 4.6
Anthropic
 $0.743750 (rounded ~ $0.74) ↑ 479.6% more ↑ 66.7% more
#11 Gemini 2.5 Pro
Google
 $0.868750 (rounded ~ $0.87) ↑ 577% more ↑ 94.7% more
#12 Gemini 3.1 Pro
Google
 $1.090000 ↑ 749.4% more ↑ 144.3% more
#13 GPT-5.4
OpenAI
 $1.362500 (rounded ~ $1.36) ↑ 961.8% more ↑ 205.3% more
#14 GPT-5.4 Thinking
OpenAI
 $1.362500 (rounded ~ $1.36) ↑ 961.8% more ↑ 205.3% more
#15 GPT-5.5
OpenAI
 $2.725000 (rounded ~ $2.73) ↑ 2023.5% more ↑ 510.6% more
#16 GPT-5.5
OpenAI
 $2.725000 (rounded ~ $2.73) ↑ 2023.5% more ↑ 510.6% more
🏆

Gemini 3.1 Flash Lite
Google

$0.043438 (rounded ~ $0.04)
vs DeepSeek V4 (Engram): ↓ 66.2%
vs Claude Sonnet 4.6: ↓ 90.3%
🥈

Gemini 2.5 Flash
Google

$0.069625
vs DeepSeek V4 (Engram): ↓ 45.7%
vs Claude Sonnet 4.6: ↓ 84.4%
🥉

Grok 4.3
xAI

$0.092188 (rounded ~ $0.09)
vs DeepSeek V4 (Engram): ↓ 28.2%
vs Claude Sonnet 4.6: ↓ 79.3%
#4

Grok 4.20 Beta
xAI

$0.197500 (rounded ~ $0.20)
vs DeepSeek V4 (Engram): ↑ 53.9%
vs Claude Sonnet 4.6: ↓ 55.7%
#5

Gemini 3.5 Flash
Google

$0.260625
vs DeepSeek V4 (Engram): ↑ 103.1%
vs Claude Sonnet 4.6: ↓ 41.6%
#6

Gemini 3.1 Flash
Google

$0.347500 (rounded ~ $0.35)
vs DeepSeek V4 (Engram): ↑ 170.8%
vs Claude Sonnet 4.6: ↓ 22.1%
#7

Claude Sonnet 4.6
Anthropic

$0.446250 (rounded ~ $0.45)
vs DeepSeek V4 (Engram): ↑ 247.7%
vs Claude Sonnet 4.6: Same
#8

Claude Opus 4.7
Anthropic

$0.743750 (rounded ~ $0.74)
vs DeepSeek V4 (Engram): ↑ 479.6%
vs Claude Sonnet 4.6: ↑ 66.7%
#9

Claude Opus 4.8
Anthropic

$0.743750 (rounded ~ $0.74)
vs DeepSeek V4 (Engram): ↑ 479.6%
vs Claude Sonnet 4.6: ↑ 66.7%
#10

Claude Opus 4.6
Anthropic

$0.743750 (rounded ~ $0.74)
vs DeepSeek V4 (Engram): ↑ 479.6%
vs Claude Sonnet 4.6: ↑ 66.7%
#11

Gemini 2.5 Pro
Google

$0.868750 (rounded ~ $0.87)
vs DeepSeek V4 (Engram): ↑ 577%
vs Claude Sonnet 4.6: ↑ 94.7%
#12

Gemini 3.1 Pro
Google

$1.090000
vs DeepSeek V4 (Engram): ↑ 749.4%
vs Claude Sonnet 4.6: ↑ 144.3%
#13

GPT-5.4
OpenAI

$1.362500 (rounded ~ $1.36)
vs DeepSeek V4 (Engram): ↑ 961.8%
vs Claude Sonnet 4.6: ↑ 205.3%
#14

GPT-5.4 Thinking
OpenAI

$1.362500 (rounded ~ $1.36)
vs DeepSeek V4 (Engram): ↑ 961.8%
vs Claude Sonnet 4.6: ↑ 205.3%
#15

GPT-5.5
OpenAI

$2.725000 (rounded ~ $2.73)
vs DeepSeek V4 (Engram): ↑ 2023.5%
vs Claude Sonnet 4.6: ↑ 510.6%
#16

GPT-5.5
OpenAI

$2.725000 (rounded ~ $2.73)
vs DeepSeek V4 (Engram): ↑ 2023.5%
vs Claude Sonnet 4.6: ↑ 510.6%
✨ 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.

Performance per Dollar

DeepSeek V4 (Engram) provides 1M context with ‘Engram Memory’ for just $0.27/1M input tokens. Claude Sonnet 4.6 is the industry favorite for ‘Agentic Coding’ reliability but costs $3.00/1M. DeepSeek V4 is the choice for high-volume automated refactoring, while Sonnet 4.6 remains the gold standard for complex system architecture.

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.