GPT-5.4 Pro OpenAI 1024000 🏔️ Context Cliff
💰 Total Cost Calculation (from Plugin)
Output: $0.540000
Output: $0.540000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 4,000 output tokens:
- Input Cost: $30.000000
- Output Cost: $0.540000
- Total Cost: $23.790000
- Cost per 1K tokens: $0.023695 (rounded ~ $0.02)
- Tokens per dollar: 42,203 tokens
- Context Window: 1024000 tokens
Speed & Performance Analysis
With a processing speed of 350 tokens per second and 250ms time to first token:
- Processing Time: 49 minutes, 43.49 seconds
- Latency: 250 milliseconds to first token
- Base Throughput: 350 tokens/second
- Effective Throughput: 337 tokens/second (temperature-adjusted)
Best Use Cases
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Financial Data Extraction at Scale
For data analysts tasked with converting hundreds of 10-K filings into structured SQL databases, the primary challenge is the density of the information. Financial reports contain complex tables, nested footnotes, and non-standardized GAAP reconciliations that require sophisticated reasoning capabilities. Using a high-tier model ensures that the nuances of cash flow statements and balance sheet line items are captured without the loss of detail common in smaller models.
When processing 1M tokens of financial data, the ability to maintain contextual awareness across an entire document is vital. This model is specifically engineered for high-stakes reasoning where accuracy is non-negotiable. Analysts should prioritize this option when the workload involves generating complex SQL schemas from disparate document sections or when performing deep-dive earnings analysis that requires cross-referencing multiple fiscal years. The model’s strength lies in its thinking capabilities, allowing it to navigate the linguistic noise of annual reports to extract pure, structured data. This makes it a robust choice for enterprise pipelines where the cost of a missed data point far outweighs the processing overhead. Additionally, the large context window allows for the ingestion of entire filings in a single pass, reducing the need for complex chunking strategies that often break the continuity of financial narratives.