Sonar Deep Research vs GPT-5.2 Pro: Discovery vs Creation

Sonar Deep Research vs GPT-5.2 Pro
Complete Comparison: 1,000,000 input tokens × 1,000,000 output tokens
Comparison Mode

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

Comparison Criteria Sonar Deep Research
Perplexity
GPT-5.2 Pro
OpenAI
Calculation Results (Current Inputs)
Input Tokens 1,000,000 1,000,000
Output Tokens 1,000,000 1,000,000
Cost Breakdown
Input Cost $2.000000Best $21.000000Worst
Output Cost $8.000000Best $168.000000Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $10.000000 Best Value $189.000000 Most Expensive
Processing Time 2 hours, 55 minutes, 0.18 seconds Slowest 1 hour, 40 minutes, 0.18 seconds Fastest
Tokens per Second 200Slowest 350Fastest
Time to First Token 300ms Worst 250ms Best
Cost per 1K tokens $0.005000 (rounded ~ $0.01)Best $0.094500 (rounded ~ $0.09)Worst
Tokens per Dollar 200,000Best Value 10,582Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $2.000000Best $21.000000Worst
Output Cost / 1M (Base) $8.000000Best $168.000000Worst
Input Cost / 1M (Optimized) $2.000000Best
Optimizations: No optimizations applied
$21.000000Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $8.000000Best
Optimizations: No optimizations applied
$168.000000Worst
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✗ Not Supported ✓ Supported
Caching Support ✗ Not Supported ✓ Supported
Batch API Support ✗ Not Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
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.

Click Recalculate to update after making changes

ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.

Select AI Model

Sonar Deep Research
PerplexityMax Context: 1,000,000 tokens
$2 / $8 + citations research pricing
▼
▼
Use Batch API (50% discount)
0%
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

$10.000000 Total Cost
$2.000000 Input Cost
$8.000000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
2,000,000Total Tokens
$0.005000Cost per 1K
200,000Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

175m 0s Processing Time
200 Tokens/Second
300ms Time to First Token
190 Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 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.

Sonar Deep Research Perplexity 1000000

$10.000000
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
🔧 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
✗ Not Available

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $10.000000 Input: $2.000000
Output: $8.000000
Optimized Cost $10.000000 Input: $2.000000
Output: $8.000000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $2.000000
  • Output Cost: $8.000000
  • Total Cost: $10.000000
  • Cost per 1K tokens: $0.005000 (rounded ~ $0.01)
  • Tokens per dollar: 200,000 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, 55 minutes, 0.18 seconds
  • Latency: 300 milliseconds to first token
  • Base Throughput: 200 tokens/second
  • Effective Throughput: 190 tokens/second (temperature-adjusted)

Best Use Cases

Investigative JournalismAcademic Verification

Want this applied to YOUR actual stack?

This calculator shows the math for Sonar Deep Research. 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 →

GPT-5.2 Pro OpenAI

$189.000000
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 128,000 tokens. Budgeting mode active.
🔧 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) $189.000000 Input: $21.000000
Output: $168.000000
Optimized Cost $189.000000 Input: $21.000000
Output: $168.000000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $21.000000
  • Output Cost: $168.000000
  • Total Cost: $189.000000
  • Cost per 1K tokens: $0.094500 (rounded ~ $0.09)
  • Tokens per dollar: 10,582 tokens
  • Context Window: 128000 tokens

Speed & Performance Analysis

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

  • Processing Time: 1 hour, 40 minutes, 0.18 seconds
  • Latency: 250 milliseconds to first token
  • Base Throughput: 350 tokens/second
  • Effective Throughput: 333 tokens/second (temperature-adjusted)

Best Use Cases

Investigative JournalismAcademic Verification

Want this applied to YOUR actual stack?

This calculator shows the math for GPT-5.2 Pro. 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 Sonar Deep Research
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000,000
Tools: Enabled
Rank AI Model & Provider Total Cost vs Sonar Deep Research vs GPT-5.2 Pro
🏆 Grok 4.20 Beta
xAI
 $8.000000 Best Value ↓ 20% cheaper ↓ 95.8% cheaper
🥈 Gemini 2.5 Pro
Google
 $17.500000 ↑ 75% more ↓ 90.7% cheaper
🥉 Gemini 2.5 Pro
Google
 $17.500000 ↑ 75% more ↓ 90.7% cheaper
🏆

Grok 4.20 Beta
xAI

$8.000000
vs Sonar Deep Research: ↓ 20%
vs GPT-5.2 Pro: ↓ 95.8%
🥈

Gemini 2.5 Pro
Google

$17.500000
vs Sonar Deep Research: ↑ 75%
vs GPT-5.2 Pro: ↓ 90.7%
🥉

Gemini 2.5 Pro
Google

$17.500000
vs Sonar Deep Research: ↑ 75%
vs GPT-5.2 Pro: ↓ 90.7%
✨ 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.

The Answer Engine vs The Creator

Perplexity’s Sonar Deep Research is built for one purpose: synthesizing the world’s current information into verified reports with citations. While GPT-5.2 Pro can browse the web, it is fundamentally a generative model that prioritizes logical output over source verification. In 2026, Sonar is the gold standard for investigative journalism and academic search, while GPT-5.2 Pro remains the superior tool for taking that information and turning it into a structured business plan or creative asset.

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 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.