Autonomous DevOps: 24/7 Incident Response

o4-mini vs deepseek-v3.2
Complete Comparison: 100,000 input tokens × 10,000 output tokens
Comparison Mode (Custom field comparison)

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

Comparison Criteria o4-mini
OpenAI
deepseek-v3.2
DeepSeek
Input Parameters Applied
Input Tokens 100,000 100,000
Output Tokens 10,000 10,000
Calculation Results
Input Cost $0.110000 Worst $0.028000 (rounded ~ 0.03) Best
Output Cost $0.044000 (rounded ~ 0.04) Worst $0.004200 (rounded ~ 0.00) Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $0.204000 (rounded ~ 0.20) Most Expensive $0.082200 (rounded ~ 0.08) Best Value
Processing Time 10 minutes, 17.00 seconds Slowest 2 minutes, 51.00 seconds Fastest
Tokens per Second 180 Slowest 650 Fastest
Time to First Token 280ms Worst 110ms Best
Cost per 1K tokens $0.001855 (rounded ~ 0.00) Worst $0.000747 Best
Tokens per Dollar 539,216 Worst Value 1,338,200 Best Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.100000 Worst $0.280000 Best
Output Cost / 1M (Base) $4.400000 Worst $0.420000 Best
Input Cost / 1M (Optimized) $1.100000 Worst
Optimizations: No optimizations applied
$0.280000 Best
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $4.400000 Worst
Optimizations: No optimizations applied
$0.420000 Best
Optimizations: No optimizations applied
Capabilities
Caching Support ✓ Supported ✓ Supported
Batch API Support Available Available
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
Scroll horizontally to see all data

🔄 Compare Different AI Models

1

First Model

2

Second Model

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All other parameters will be preserved from the current comparison.

Select AI Model

o4-mini
OpenAIMax Context: 200,000 tokens
Input: $1.100000 / 1M
Output: $4.400000 / 1M

Calculate Token Costs

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
$0.110000Input Cost
$0.044000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
110,000Total Tokens
$0.001855Cost per 1K
539,216Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

10m 17sProcessing Time
180Tokens/Second
280msTime to First Token
178Effective 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.

o4-mini OpenAI

$0.204000 (rounded ~ 0.20)
Total Cost
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
Caching
✓ Available
90% savings

💰 Total Cost Calculation

Base Cost (No Optimizations) $0.204000 (rounded ~ 0.20) Input: $0.110000
Output: $0.044000 (rounded ~ 0.04)
Optimized Cost $0.204000 (rounded ~ 0.20) Input: $0.110000
Output: $0.044000 (rounded ~ 0.04)
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 100,000 input tokens and 10,000 output tokens:

  • Input Cost: $0.110000
  • Output Cost: $0.044000 (rounded ~ 0.04)
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $0.204000 (rounded ~ 0.20)
  • Cost per 1K tokens: $0.001855 (rounded ~ 0.00)
  • Tokens per dollar: 539,216 tokens
  • Context Window: 200000 tokens

Speed & Performance Analysis

With a processing speed of 180 tokens per second and 280ms time to first token:

  • Processing Time: 10 minutes, 17.00 seconds
  • Latency: 280 milliseconds to first token
  • Base Throughput: 180 tokens/second
  • Effective Throughput: 178 tokens/second

Best Use Cases

DevOpsSREInfrastructure MonitoringCybersecurity

deepseek-v3.2 DeepSeek

$0.082200 (rounded ~ 0.08)
Total Cost
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
Caching
✓ Available
90% savings

💰 Total Cost Calculation

Base Cost (No Optimizations) $0.082200 (rounded ~ 0.08) Input: $0.028000 (rounded ~ 0.03)
Output: $0.004200 (rounded ~ 0.00)
Optimized Cost $0.082200 (rounded ~ 0.08) Input: $0.028000 (rounded ~ 0.03)
Output: $0.004200 (rounded ~ 0.00)
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 100,000 input tokens and 10,000 output tokens:

  • Input Cost: $0.028000 (rounded ~ 0.03)
  • Output Cost: $0.004200 (rounded ~ 0.00)
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $0.082200 (rounded ~ 0.08)
  • Cost per 1K tokens: $0.000747
  • Tokens per dollar: 1,338,200 tokens
  • Context Window: 128000 tokens

Speed & Performance Analysis

With a processing speed of 650 tokens per second and 110ms time to first token:

  • Processing Time: 2 minutes, 51.00 seconds
  • Latency: 110 milliseconds to first token
  • Base Throughput: 650 tokens/second
  • Effective Throughput: 644 tokens/second

Best Use Cases

DevOpsSREInfrastructure MonitoringCybersecurity

Real-Time Infrastructure Monitoring Costs

Using o4-mini’s logical troubleshooting for continuous DevOps monitoring with secure tool-calling and reasoning capabilities.

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.