Processing or generating 100,000 words (approximately 133,300 tokens) with Microsoft Phi-4 (14B) ranges from $0.003333 (cached input) to $0.04 (full generation).
Quick answer
For 100,000 words, Microsoft Phi-4 (14B) processes approximately 133,300 tokens. That costs $0.0133 as uncached input, $0.003333 with the modeled cache discount, or $0.04 when generated as output.
Method & trust
The estimate converts the selected English word count with the model tokenizer family, then applies the published input/output price per million tokens. Real prompts vary with code, formatting, language, and system instructions.
You send 100,000 words as prompt context, documentation, or background knowledge.
Microsoft Phi-4 (14B) drafts a complete 100,000 words article, chapter, or code module.
80,000 words input prompt + 20,000 words output reply.
| Model | Provider | Input Cost (100,000 words) | Cached Input Cost | Output Cost (100,000 words) | Context Limit |
|---|---|---|---|---|---|
| Microsoft Phi-4 (14B) (Current) | microsoft | $0.0133 | $0.003333 | $0.04 | 16,384 |
| GPT-5.6 Luna | openai | $0.0256 | $0.00256 | $0.1536 | 1,050,000 |
| GPT-5.4 mini | openai | $0.096 | $0.0096 | $0.576 | 256,000 |
| GPT-5.4 nano | openai | $0.0256 | $0.00256 | $0.16 | 128,000 |
| GPT-4o mini | openai | $0.0192 | $0.0096 | $0.0768 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.132 | $0.0132 | $0.66 | 1,000,000 |
For Microsoft Phi-4 (14B) (cl100k_base tokenizer), 100,000 words is approximately 133,300 tokens (an average ratio of 1.33 tokens per word in English). Code, technical vocabulary, and non-English scripts will have higher token densities.
Sending 100,000 words as input costs $0.0133 (or $0.003333 with prompt caching). Generating 100,000 words as output costs $0.04. Output tokens are more expensive because autoregressive token generation requires significantly more computation per token.
Yes! If your input text is part of a repeated context, prompt caching saves 50% to 90% (costing $0.003333). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.006665 for input, $0.02 for output).
At an average human reading speed of 250 words per minute, 100,000 words takes approximately 400 minutes to read. In contrast, Microsoft Phi-4 (14B) can process or generate this text in seconds.