GPT-5.4 Mini OpenAI
💰 Total Cost Calculation (from Plugin)
Output: $0.004500
Output: $0.004500
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 4,000 output tokens:
- Input Cost: $0.018750 (rounded ~ $0.02)
- Output Cost: $0.004500
- Total Cost: $0.015656 (rounded ~ $0.02)
- Cost per 1K tokens: $0.000151
- Tokens per dollar: 6,642,715 tokens
- Context Window: 400000 tokens
Speed & Performance Analysis
With a processing speed of 500 tokens per second and 180ms time to first token:
- Processing Time: 3 minutes, 42.74 seconds
- Latency: 180 milliseconds to first token
- Base Throughput: 500 tokens/second
- Effective Throughput: 467 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to GPT-5.4 Mini| Rank | AI Model & Provider | Total Cost | vs GPT-5.4 Mini |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001788 Best Value | ↓ 88.6% cheaper |
| 🥈 |
Grok Code Fast 1
xAI
|
$0.004475 | ↓ 71.4% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.005219 (rounded ~ $0.01) | ↓ 66.7% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.006963 (rounded ~ $0.01) | ↓ 55.5% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.008938 (rounded ~ $0.01) | ↓ 42.9% cheaper |
| #6 |
o4-mini Deep Research
OpenAI
|
$0.018875 (rounded ~ $0.02) | ↑ 20.6% more |
| #7 |
Claude Haiku 4.5
Anthropic
|
$0.019875 | ↑ 26.9% more |
| #8 |
o4-mini
OpenAI
|
$0.020763 | ↑ 32.6% more |
| #9 |
Gemini 3.1 Flash
Google
|
$0.020875 | ↑ 33.3% more |
| #10 |
Grok 4.3
xAI
|
$0.021094 (rounded ~ $0.02) | ↑ 34.7% more |
| #11 |
Gemini 3.5 Flash
Google
|
$0.031313 (rounded ~ $0.03) | ↑ 100% more |
| #12 |
Grok 4.20 Beta
xAI
|
$0.035750 (rounded ~ $0.04) | ↑ 128.3% more |
| #13 |
GPT-5.3 Codex Spark
OpenAI
|
$0.040031 | ↑ 155.7% more |
| #14 |
GPT-5.3 Instant
OpenAI
|
$0.040031 | ↑ 155.7% more |
| #15 |
Gemini 2.5 Pro
Google
|
$0.057188 (rounded ~ $0.06) | ↑ 265.3% more |
| #16 |
Claude Sonnet 4.6
Anthropic
|
$0.059625 | ↑ 280.8% more |
| #17 |
Gemini 3.1 Pro
Google
|
$0.083500 (rounded ~ $0.08) | ↑ 433.3% more |
| #18 |
Claude Opus 4.7
Anthropic
|
$0.099375 | ↑ 534.7% more |
| #19 |
Claude Opus 4.8
Anthropic
|
$0.099375 | ↑ 534.7% more |
| #20 |
Claude Opus 4.6
Anthropic
|
$0.099375 | ↑ 534.7% more |
| #21 |
GPT-5.4
OpenAI
|
$0.104375 (rounded ~ $0.10) | ↑ 566.7% more |
| #22 |
GPT-5.4 Thinking
OpenAI
|
$0.104375 (rounded ~ $0.10) | ↑ 566.7% more |
| #23 |
GPT-5.5 Instant
OpenAI
|
$0.104375 (rounded ~ $0.10) | ↑ 566.7% more |
| #24 |
o3 Deep Research
OpenAI
|
$0.188750 (rounded ~ $0.19) | ↑ 1105.6% more |
| #25 |
GPT-5.5
OpenAI
|
$0.208750 (rounded ~ $0.21) | ↑ 1233.3% more |
| #26 |
o3 Pro
OpenAI
|
$0.377500 (rounded ~ $0.38) | ↑ 2311.2% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.480375 | ↑ 2968.3% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$0.480375 | ↑ 2968.3% more |
Mistral Small 3 Mistral AI
Grok Code Fast 1 xAI
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Gemini 3.1 Flash Google
Grok 4.3 xAI
Gemini 3.5 Flash Google
Grok 4.20 Beta xAI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
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-5.4 Thinking 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
Evaluating OpenAI’s Value: GPT-5.4 Mini for 100,000 Tokens
This entry examines the cost implications of using OpenAI’s GPT-5.4 Mini for processing approximately 100,000 tokens. This volume is substantial enough for analyzing detailed code reviews, comprehensive documentation, or longer scripts, making it a relevant benchmark for academic researchers and developers building more sophisticated AI tools.
GPT-5.4 Mini: Balanced Performance and Price
GPT-5.4 Mini offers a compelling balance of OpenAI’s advanced capabilities with a more accessible price point compared to its Pro counterparts. It features a generous 400,000 token context window, ensuring that the 100,000 token input is well within its limits. The pricing stands at $0.75 per 1 million input tokens, translating to an estimated cost of $0.075 for processing 100,000 tokens.
This model is equipped with capabilities for text, vision, tools, thinking, and reasoning, making it highly suitable for nuanced code analysis. The ‘thinking’ and ‘reasoning’ attributes are particularly valuable for understanding complex code logic, suggesting improvements, and generating insights beyond simple summarization.
- Model Name: GPT-5.4 Mini
- Provider: OpenAI
- Context Window: 400,000 tokens
- Pricing (per 1M tokens): $0.75 (input) / $4.50 (output)
- Estimated Cost for 100K Tokens: ~$0.075
- Key Capabilities: text, vision, tools, thinking, reasoning
Code Review Assistant Application
For a code review assistant, GPT-5.4 Mini provides a robust foundation. It can analyze code diffs, understand the intent behind changes, identify potential bugs or security vulnerabilities, and even suggest refactoring or optimization strategies. The inclusion of ‘vision’ capabilities could potentially be leveraged if code snippets are part of visual diagrams or UI mockups, though its primary strength remains in text-based code understanding.
The model’s ability to use tools significantly enhances its utility. For code review, this could mean integrating with linters, static analysis tools, or even external documentation lookup services to provide more comprehensive feedback. The 100,000 token input capacity allows for the analysis of substantial code files or multiple related changes within a single request.
Academic researchers and indie developers can leverage GPT-5.4 Mini to build powerful prototypes that mimic professional code review workflows, benefiting from OpenAI’s advanced reasoning and tool-use capabilities without the premium cost of the highest-tier models.
Best Use Cases: Advanced text analysis, code review and generation, intelligent agents requiring reasoning and tool integration, and prototyping complex AI applications on a moderate budget.