GPT-5.4 Thinking OpenAI 1024000
💰 Total Cost Calculation (from Plugin)
Output: $0.022500 (rounded ~ $0.02)
Output: $0.022500 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 20,000 input tokens and 3,000 output tokens:
- Input Cost: $0.025000 (rounded ~ $0.03)
- Output Cost: $0.022500 (rounded ~ $0.02)
- Total Cost: $0.036250 (rounded ~ $0.04)
- Cost per 1K tokens: $0.001576
- Tokens per dollar: 634,483 tokens
- Context Window: 1024000 tokens
Speed & Performance Analysis
With a processing speed of 400 tokens per second and 220ms time to first token:
- Processing Time: 1 minute, 1.71 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 374 tokens/second (temperature-adjusted)
Best Use Cases
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💰 Total Cost Calculation (from Plugin)
Output: $0.024000 (rounded ~ $0.02)
Output: $0.024000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 20,000 input tokens and 3,000 output tokens:
- Input Cost: $0.040000
- Output Cost: $0.024000 (rounded ~ $0.02)
- Total Cost: $0.064000 (rounded ~ $0.06)
- Cost per 1K tokens: $0.002783
- Tokens per dollar: 359,375 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 minutes, 3.23 seconds
- Latency: 300 milliseconds to first token
- Base Throughput: 200 tokens/second
- Effective Throughput: 187 tokens/second (temperature-adjusted)
Best Use Cases
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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.
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Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to GPT-5.4 Thinking| Rank | AI Model & Provider | Total Cost | vs GPT-5.4 Thinking | vs Sonar Deep Research |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.000500 Best Value | ↓ 98.6% cheaper | ↓ 99.2% cheaper |
| 🥈 |
Grok Code Fast 1
xAI
|
$0.001675 | ↓ 95.4% cheaper | ↓ 97.4% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.001813 | ↓ 95% cheaper | ↓ 97.2% cheaper |
| #4 |
Mistral Large 3
Mistral AI
|
$0.002500 | ↓ 93.1% cheaper | ↓ 96.1% cheaper |
| #5 |
Gemini 2.5 Flash
Google
|
$0.002700 | ↓ 92.6% cheaper | ↓ 95.8% cheaper |
| #6 |
Grok 4.3
xAI
|
$0.005313 (rounded ~ $0.01) | ↓ 85.3% cheaper | ↓ 91.7% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.005438 (rounded ~ $0.01) | ↓ 85% cheaper | ↓ 91.5% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.005750 (rounded ~ $0.01) | ↓ 84.1% cheaper | ↓ 91% cheaper |
| #9 |
o4-mini
OpenAI
|
$0.006325 (rounded ~ $0.01) | ↓ 82.6% cheaper | ↓ 90.1% cheaper |
| #10 |
Claude Haiku 4.5
Anthropic
|
$0.006500 (rounded ~ $0.01) | ↓ 82.1% cheaper | ↓ 89.8% cheaper |
| #11 |
Gemini 3.1 Flash
Google
|
$0.007250 (rounded ~ $0.01) | ↓ 80% cheaper | ↓ 88.7% cheaper |
| #12 |
Grok 4.20 Beta
xAI
|
$0.010000 | ↓ 72.4% cheaper | ↓ 84.4% cheaper |
| #13 |
Gemini 3.5 Flash
Google
|
$0.010875 | ↓ 70% cheaper | ↓ 83% cheaper |
| #14 |
GPT-5.3 Codex Spark
OpenAI
|
$0.015313 (rounded ~ $0.02) | ↓ 57.8% cheaper | ↓ 76.1% cheaper |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.015313 (rounded ~ $0.02) | ↓ 57.8% cheaper | ↓ 76.1% cheaper |
| #16 |
Claude Sonnet 4.6
Anthropic
|
$0.019500 | ↓ 46.2% cheaper | ↓ 69.5% cheaper |
| #17 |
Gemini 2.5 Pro
Google
|
$0.021875 (rounded ~ $0.02) | ↓ 39.7% cheaper | ↓ 65.8% cheaper |
| #18 |
Gemini 3.1 Pro
Google
|
$0.029000 | ↓ 20% cheaper | ↓ 54.7% cheaper |
| #19 |
Claude Opus 4.7
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↓ 10.3% cheaper | ↓ 49.2% cheaper |
| #20 |
Claude Opus 4.8
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↓ 10.3% cheaper | ↓ 49.2% cheaper |
| #21 |
Claude Opus 4.6
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↓ 10.3% cheaper | ↓ 49.2% cheaper |
| #22 |
GPT-5.4
OpenAI
|
$0.036250 (rounded ~ $0.04) | Same price | ↓ 43.4% cheaper |
| #23 |
GPT-5.5 Instant
OpenAI
|
$0.036250 (rounded ~ $0.04) | Same price | ↓ 43.4% cheaper |
| #24 |
o3 Deep Research
OpenAI
|
$0.057500 (rounded ~ $0.06) | ↑ 58.6% more | ↓ 10.2% cheaper |
| #25 |
GPT-5.5
OpenAI
|
$0.072500 (rounded ~ $0.07) | ↑ 100% more | ↑ 13.3% more |
| #26 |
o3 Pro
OpenAI
|
$0.115000 (rounded ~ $0.12) | ↑ 217.2% more | ↑ 79.7% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.183750 (rounded ~ $0.18) | ↑ 406.9% more | ↑ 187.1% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$0.183750 (rounded ~ $0.18) | ↑ 406.9% more | ↑ 187.1% more |
Mistral Small 3 Mistral AI
Grok Code Fast 1 xAI
Gemini 3.1 Flash Lite Google
Mistral Large 3 Mistral AI
Gemini 2.5 Flash Google
Grok 4.3 xAI
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
o4-mini OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
Grok 4.20 Beta xAI
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 4.6 Anthropic
Gemini 2.5 Pro Google
Gemini 3.1 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.5 Instant OpenAI
o3 Deep Research OpenAI
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Deep Analysis for Code Diffs: GPT-5.4 Thinking vs. Sonar Deep Research at 20,000 Tokens
This comparison focuses on optimizing code diff analysis by examining the performance and cost of two high-context models, GPT-5.4 Thinking and Sonar Deep Research, for processing approximately 20,000 tokens. This volume is suitable for detailed analysis of specific code logic, complex bug fixes, or performance-critical sections within a pull request, targeting academic researchers and developers focused on precision.
GPT-5.4 Thinking: Advanced Reasoning Power
OpenAI’s GPT-5.4 Thinking model offers a substantial 1,024,000 token context window, paired with powerful reasoning capabilities. Priced at $2.5 per 1 million input tokens, the cost for 20,000 tokens is approximately $0.05. This model is explicitly designed for tasks requiring deep thought, analysis, and problem-solving, making it highly relevant for understanding intricate code structures and potential issues.
- Model Name: GPT-5.4 Thinking
- Provider: OpenAI
- Context Window: 1,024,000 tokens
- Pricing (per 1M tokens): $2.50 (input) / $15.00 (output)
- Estimated Cost for 20K Tokens: ~$0.05
- Key Capabilities: text, vision, tools, thinking, reasoning
Sonar Deep Research: Factual Depth and Tools
Perplexity’s Sonar Deep Research model also provides a vast 1,000,000 token context window and is geared towards in-depth analysis. Its pricing is $2 per 1 million input tokens, resulting in an approximate cost of $0.04 for 20,000 tokens. This model excels at grounding responses in factual information and can leverage tools, which is beneficial for cross-referencing code with documentation or external knowledge bases.
- Model Name: Sonar Deep Research
- Provider: Perplexity
- Context Window: 1,000,000 tokens
- Pricing (per 1M tokens): $2.00 (input) / $8.00 (output)
- Estimated Cost for 20K Tokens: ~$0.04
- Key Capabilities: text, reasoning, tools
Code Review Optimization
For optimizing code diff analysis, both models offer significant advantages due to their large context windows and reasoning/tool-use capabilities. Sonar Deep Research is slightly more cost-effective for this specific 20K token volume, making it an attractive option for researchers prioritizing minimal spend. Its focus on deep research and factual grounding can be invaluable for ensuring code adheres to strict standards or for understanding complex algorithms.
GPT-5.4 Thinking, while marginally more expensive, offers ‘vision’ capabilities in addition to reasoning and tools. This could be a deciding factor if the code review process involves analyzing UI elements or diagrams alongside the code. Both models are well-suited for academic projects that require detailed, precise analysis of code, allowing for the creation of sophisticated AI-powered code review assistants that can identify subtle issues and suggest robust solutions.
Best Use Cases: In-depth code analysis, research requiring precise reasoning and factual grounding, and development of AI assistants for identifying complex issues in code and documentation.