Processing or generating 500 words (approximately 667 tokens) with Llama 3.1 8B Instruct ranges from $0.0000083 (cached input) to $0.000053 (full generation).
You send 500 words as prompt context, documentation, or background knowledge.
Llama 3.1 8B Instruct drafts a complete 500 words article, chapter, or code module.
400 words input prompt + 100 words output reply.
| Model | Provider | Input Cost (500 words) | Cached Input Cost | Output Cost (500 words) | Context Limit |
|---|---|---|---|---|---|
| Llama 3.1 8B Instruct (Current) | meta | $0.000033 | $0.0000083 | $0.000053 | 128,000 |
| GPT-5.6 Luna | openai | $0.000128 | $0.000013 | $0.000768 | 1,050,000 |
| GPT-5.4 mini | openai | $0.00048 | $0.000048 | $0.00288 | 256,000 |
| GPT-5.4 nano | openai | $0.000128 | $0.000013 | $0.0008 | 128,000 |
| GPT-4o mini | openai | $0.000096 | $0.000048 | $0.000384 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.00066 | $0.000066 | $0.0033 | 1,000,000 |
For Llama 3.1 8B Instruct (tiktoken_cl100k tokenizer), 500 words is approximately 667 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 500 words as input costs $0.000033 (or $0.0000083 with prompt caching). Generating 500 words as output costs $0.000053. 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 $0.0000083). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.000017 for input, $0.000027 for output).
At an average human reading speed of 250 words per minute, 500 words takes approximately 2 minutes to read. In contrast, Llama 3.1 8B Instruct can process or generate this text in seconds.