Processing or generating 25,000 words (approximately 33,325 tokens) with Llama 3.1 8B Instruct ranges from $0.000417 (cached input) to $0.002666 (full generation).
You send 25,000 words as prompt context, documentation, or background knowledge.
Llama 3.1 8B Instruct drafts a complete 25,000 words article, chapter, or code module.
20,000 words input prompt + 5,000 words output reply.
| Model | Provider | Input Cost (25,000 words) | Cached Input Cost | Output Cost (25,000 words) | Context Limit |
|---|---|---|---|---|---|
| Llama 3.1 8B Instruct (Current) | meta | $0.001666 | $0.000417 | $0.002666 | 128,000 |
| GPT-5.6 Luna | openai | $0.0064 | $0.00064 | $0.0384 | 1,050,000 |
| GPT-5.4 mini | openai | $0.024 | $0.0024 | $0.144 | 256,000 |
| GPT-5.4 nano | openai | $0.0064 | $0.00064 | $0.04 | 128,000 |
| GPT-4o mini | openai | $0.0048 | $0.0024 | $0.0192 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.033 | $0.0033 | $0.165 | 1,000,000 |
For Llama 3.1 8B Instruct (tiktoken_cl100k tokenizer), 25,000 words is approximately 33,325 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 25,000 words as input costs $0.001666 (or $0.000417 with prompt caching). Generating 25,000 words as output costs $0.002666. 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 $0.000417). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.000833 for input, $0.001333 for output).
At an average human reading speed of 250 words per minute, 25,000 words takes approximately 100 minutes to read. In contrast, Llama 3.1 8B Instruct can process or generate this text in seconds.