Temperature Impact: Speed vs Cost Analysis 2026

gpt-5 vs gemini-2.5-flash
Complete Comparison: 200,000 input tokens × 100,000 output tokens
Comparison Mode (Custom field comparison)

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

Comparison Criteria gpt-5
OpenAI
gemini-2.5-flash
Google
Input Parameters Applied
Input Tokens 200,000 200,000
Output Tokens 100,000 100,000
Calculation Results
Input Cost $0.350000 Best $0.400000 Worst
Output Cost $1.400000 Worst $1.200000 Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $1.750000 Most Expensive $1.600000 Best Value
Processing Time 11 minutes, 53.00 seconds Slowest 10 minutes, 42.00 seconds Fastest
Tokens per Second 450 Slowest 500 Fastest
Time to First Token 200ms 200ms
Cost per 1K tokens $0.005833 (rounded ~ 0.01) Worst $0.005333 (rounded ~ 0.01) Best
Tokens per Dollar 171,429 Worst Value 187,500 Best Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.750000 Best $2.000000 Worst
Output Cost / 1M (Base) $14.000000 Worst $12.000000 Best
Input Cost / 1M (Optimized) $1.750000 Best
Optimizations: No optimizations applied
$2.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $14.000000 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

1

First Model

2

Second Model

Select providers and models above, then click "Compare Models" to update the comparison.
All other parameters will be preserved from the current comparison.

Select AI Model

Gpt 5
OpenAIMax Context: 400,000 tokens
Input: $1.750000 / 1M
Output: $14.000000 / 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
$1.750000Total Cost
$0.350000Input Cost
$1.400000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
300,000Total Tokens
$0.005833Cost per 1K
171,429Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
11m 53sProcessing Time
450Tokens/Second
200msTime to First Token
421Effective 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.

gpt-5 OpenAI

$1.750000
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) $1.750000 Input: $0.350000
Output: $1.400000
Optimized Cost $1.750000 Input: $0.350000
Output: $1.400000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 200,000 input tokens and 100,000 output tokens:

  • Input Cost: $0.350000
  • Output Cost: $1.400000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $1.750000
  • Cost per 1K tokens: $0.005833 (rounded ~ 0.01)
  • Tokens per dollar: 171,429 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: 11 minutes, 53.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 421 tokens/second

Best Use Cases

Temperature tuningPerformance optimization

gemini-2.5-flash Google 2000000

$1.600000
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) $1.600000 Input: $0.400000
Output: $1.200000
Optimized Cost $1.600000 Input: $0.400000
Output: $1.200000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 200,000 input tokens and 100,000 output tokens:

  • Input Cost: $0.400000
  • Output Cost: $1.200000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $1.600000
  • Cost per 1K tokens: $0.005333 (rounded ~ 0.01)
  • Tokens per dollar: 187,500 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: 10 minutes, 42.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 467 tokens/second

Best Use Cases

Temperature tuningPerformance optimization

Performance-Cost Trade-off Analysis

Analyzing how temperature settings affect both speed and effective token costs.

Temperature Analysis

  • Temperature 0.0: Base speed, 100% efficiency
  • Temperature 0.5: 5% slower, 95% efficiency
  • Temperature 1.0: 10% slower, 90% efficiency
  • Effective cost: Speed reduction = higher $/token

Temperature Optimization

Low: Factual tasks. Medium: Balanced. High: Creative tasks.

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.