Gemini 3 Pro vs GPT-5.2 Pro reasoning costs

gpt-5-2-thinking vs gemini-3-pro
Complete Comparison: 80,000 input tokens × 30,000 output tokens
Comparison Mode (Custom field comparison)

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

Comparison Criteria gpt-5-2-thinking
OpenAI
gemini-3-pro
Google
Input Parameters Applied
Input Tokens 80,000 80,000
Output Tokens 30,000 30,000
Calculation Results
Input Cost $1.680000 Worst $0.160000 Best
Output Cost $5.040000 Worst $0.360000 Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $6.770000 Most Expensive $0.570000 Best Value
Processing Time 5 minutes, 23.00 seconds Slowest 3 minutes, 46.00 seconds Fastest
Tokens per Second 350 Slowest 500 Fastest
Time to First Token 250ms Worst 200ms Best
Cost per 1K tokens $0.061545 (rounded ~ 0.06) Worst $0.005182 (rounded ~ 0.01) Best
Tokens per Dollar 16,248 Worst Value 192,982 Best Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $21.000000 Worst $2.000000 Best
Output Cost / 1M (Base) $168.000000 Worst $12.000000 Best
Input Cost / 1M (Optimized) $21.000000 Worst
Optimizations: No optimizations applied
$2.000000 Best
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $168.000000 Worst
Optimizations: No optimizations applied
$12.000000 Best
Optimizations: No optimizations applied
Capabilities
Caching Support ✓ Supported ✗ Not Supported
Batch API Support Available ✗ Not Supported
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

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2

Second Model

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All other parameters will be preserved from the current comparison.

Select AI Model

GPT-5.2 Thinking
OpenAIMax Context: 400,000 tokens
Input: $21.000000 / 1M
Output: $168.000000 / 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
$1.680000Input Cost
$5.040000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
110,000Total Tokens
$0.061545Cost per 1K
16,248Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

5m 23sProcessing Time
350Tokens/Second
250msTime to First Token
340Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

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🔄 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.

gpt-5-2-thinking OpenAI

$6.770000
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) $6.770000 Input: $1.680000
Output: $5.040000
Optimized Cost $6.770000 Input: $1.680000
Output: $5.040000
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 30,000 output tokens:

  • Input Cost: $1.680000
  • Output Cost: $5.040000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $6.770000
  • Cost per 1K tokens: $0.061545 (rounded ~ 0.06)
  • Tokens per dollar: 16,248 tokens
  • Context Window: 400000 tokens

Speed & Performance Analysis

With a processing speed of 350 tokens per second and 250ms time to first token:

  • Processing Time: 5 minutes, 23.00 seconds
  • Latency: 250 milliseconds to first token
  • Base Throughput: 350 tokens/second
  • Effective Throughput: 340 tokens/second

Best Use Cases

ResearchEngineeringMathematicsAlgorithms

gemini-3-pro Google 2000000

$0.570000
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) $0.570000 Input: $0.160000
Output: $0.360000
Optimized Cost $0.570000 Input: $0.160000
Output: $0.360000
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 30,000 output tokens:

  • Input Cost: $0.160000
  • Output Cost: $0.360000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $0.570000
  • Cost per 1K tokens: $0.005182 (rounded ~ 0.01)
  • Tokens per dollar: 192,982 tokens
  • Context Window: 2000000 tokens

Speed & Performance Analysis

With a processing speed of 500 tokens per second and 200ms time to first token:

  • Processing Time: 3 minutes, 46.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 485 tokens/second

Best Use Cases

ResearchEngineeringMathematicsAlgorithms

Reasoning Model Cost Comparison

Top-tier reasoning models from Google and OpenAI. Different approaches to complex problem solving with varying price points.

Performance Analysis

  • GPT-5.2 Pro: $21/M input, $168/M output
  • Gemini 3 Pro: $2-4/M input (tiered)
  • GPT-5.2 Pro: 350 tokens/sec
  • Gemini 3 Pro: 400 tokens/sec

High-Stakes Applications

Scientific research, complex engineering, mathematical proofs, algorithmic design.

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.