gpt-40-mini OpenAI
💰 Total Cost Calculation
Output: $5.000000
Output: $5.000000
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis
For 500,000 input tokens and 200,000 output tokens:
- Input Cost: $2.500000
- Output Cost: $5.000000
- Unit Cost: $0.000000
- Service Fees: $0.000000
- Total Cost: $7.500000
- Cost per 1K tokens: $0.010714
- Tokens per dollar: 93,333 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: 24 minutes, 16.00 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 500 tokens/second
- Effective Throughput: 481 tokens/second
Best Use Cases
llama-4-scout-17b Meta 10000000
💰 Total Cost Calculation
Output: $1.000000
Output: $1.000000
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis
For 500,000 input tokens and 200,000 output tokens:
- Input Cost: $0.500000
- Output Cost: $1.000000
- Unit Cost: $0.000000
- Service Fees: $0.000000
- Total Cost: $1.500000
- Cost per 1K tokens: $0.002143 (rounded ~ 0.00)
- Tokens per dollar: 466,667 tokens
- Context Window: 10000000 tokens
Speed & Performance Analysis
With a processing speed of 600 tokens per second and 120ms time to first token:
- Processing Time: 20 minutes, 13.00 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 600 tokens/second
- Effective Throughput: 577 tokens/second
Best Use Cases
Open Source vs API Cost Analysis
Comparing self-hosted open source models with managed API services. Different cost structures for deployment flexibility.
Total Cost Comparison
- Llama 4 (Self-hosted): Infrastructure + maintenance
- GPT-4.5 API: Pay-per-token usage
- Break-even point: 5M tokens/month
- Scalability considerations
Deployment Scenarios
Enterprise internal tools, data-sensitive applications, high-volume workloads, custom fine-tuning.