Sonar Deep Research vs GPT-5.2: Search vs. Pure Generation

Sonar Deep Research vs GPT-5.2
Complete Comparison: 1,000,000 input tokens × 1,000,000 output tokens
Comparison Mode (Custom field comparison)

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

Comparison Criteria Sonar Deep Research
Perplexity
GPT-5.2
OpenAI
Input Parameters Applied
Input Tokens 1,000,000 1,000,000
Output Tokens 1,000,000 1,000,000
Calculation Results
Input Cost $1.000000 Best $5.000000 Worst
Output Cost $5.000000 Best $25.000000 Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.050000 $0.050000
Total Cost $6.050000 Best Value $30.050000 Most Expensive
Processing Time 2 hours, 58 minutes, 20.00 seconds Slowest 1 hour, 11 minutes, 20.00 seconds Fastest
Tokens per Second 200 Slowest 500 Fastest
Time to First Token 300ms Worst 200ms Best
Cost per 1K tokens $0.003025 (rounded ~ 0.00) Best $0.015025 (rounded ~ 0.02) Worst
Tokens per Dollar 330,579 Best Value 66,556 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.000000 Best $5.000000 Worst
Output Cost / 1M (Base) $5.000000 Best $25.000000 Worst
Input Cost / 1M (Optimized) $1.000000 Best
Optimizations: No optimizations applied
$5.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $5.000000 Best
Optimizations: No optimizations applied
$25.000000 Worst
Optimizations: No optimizations applied
Capabilities
Caching Support ✗ Not Supported ✗ Not Supported
Batch API Support ✗ Not Supported ✗ Not Supported
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
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All other parameters will be preserved from the current comparison.

ℹ️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 1,000,000 tokens.

Select AI Model

Sonar Deep Research
PerplexityMax Context: 1,000,000 tokens
Input: $1.000000 / 1M
Output: $5.000000 / 1M

Calculate Token Costs

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▼
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
$6.050000Total Cost
$1.000000Input Cost
$5.000000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
2,000,000Total Tokens
$0.003025Cost per 1K
330,579Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
178m 20sProcessing Time
200Tokens/Second
300msTime to First Token
187Effective Speed

Model Comparison

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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.

Sonar Deep Research Perplexity 1000000

$6.050000
Total Cost
⚠️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 1,000,000 tokens.
👁️
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) $6.050000 Input: $1.000000
Output: $5.000000
Optimized Cost $6.050000 Input: $1.000000
Output: $5.000000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 1,000,000 input tokens and 1,000,000 output tokens:

  • Input Cost: $1.000000
  • Output Cost: $5.000000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $6.050000
  • Cost per 1K tokens: $0.003025 (rounded ~ 0.00)
  • Tokens per dollar: 330,579 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 200 tokens per second and 300ms time to first token:

  • Processing Time: 2 hours, 58 minutes, 20.00 seconds
  • Latency: 300 milliseconds to first token
  • Base Throughput: 200 tokens/second
  • Effective Throughput: 187 tokens/second

Best Use Cases

Fact CheckingMarket ResearchReports

GPT-5.2 OpenAI

$30.050000
Total Cost
⚠️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 400,000 tokens.
👁️
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) $30.050000 Input: $5.000000
Output: $25.000000
Optimized Cost $30.050000 Input: $5.000000
Output: $25.000000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 1,000,000 input tokens and 1,000,000 output tokens:

  • Input Cost: $5.000000
  • Output Cost: $25.000000
  • Unit Cost: $0.000000
  • Service Fees: $0.050000
  • Total Cost: $30.050000
  • Cost per 1K tokens: $0.015025 (rounded ~ 0.02)
  • Tokens per dollar: 66,556 tokens
  • Context Window: 400000 tokens

Speed & Performance Analysis

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

  • Processing Time: 1 hour, 11 minutes, 20.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 467 tokens/second

Best Use Cases

Fact CheckingMarket ResearchReports

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Factual Grounding vs Creative Synthesis

Perplexity’s Sonar Deep Research ($10.00 for 1M/1M) is fundamentally different from OpenAI’s GPT-5.2 ($15.75). Sonar uses a dedicated search pipeline to ground its responses in live web data, making it essential for market research and fact-checking. GPT-5.2 is a more powerful generative engine, better suited for taking existing data and synthesizing it into complex creative or logical formats.

Verification and Citations

Sonar’s deep citation engine ensures that every claim is verified against reliable sources. GPT-5.2, while highly logical, relies on its internal knowledge base unless connected to external tools. For journalists and analysts, Sonar offers a ‘ready-to-publish’ verification layer that GPT-5.2 requires human oversight to match. However, GPT-5.2 remains the master of complex problem solving and tool-calling automation.

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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.