Processing or generating 10,000 words (approximately 13,200 tokens) with Claude 3 Opus ranges from $0.0198 (cached input) to $0.99 (full generation).
You send 10,000 words as prompt context, documentation, or background knowledge.
Claude 3 Opus drafts a complete 10,000 words article, chapter, or code module.
8,000 words input prompt + 2,000 words output reply.
| Model | Provider | Input Cost (10,000 words) | Cached Input Cost | Output Cost (10,000 words) | Context Limit |
|---|---|---|---|---|---|
| Claude 3 Opus (Current) | anthropic | $0.198 | $0.0198 | $0.99 | 200,000 |
| GPT-5.6 Sol | openai | $0.064 | $0.0064 | $0.384 | 1,050,000 |
| GPT-5.6 Cyber | openai | $0.16 | $0.016 | $0.96 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.064 | $0.0064 | $0.384 | 512,000 |
| GPT-5.5 Pro | openai | $0.384 | $0.0384 | $2.304 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $0.256 | $0.0256 | $1.024 | 1,000,000 |
For Claude 3 Opus (claude_bpe tokenizer), 10,000 words is approximately 13,200 tokens (an average ratio of 1.32 tokens per word in English). Code, technical vocabulary, and non-English scripts will have higher token densities.
Sending 10,000 words as input costs $0.198 (or $0.0198 with prompt caching). Generating 10,000 words as output costs $0.99. 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 $0.0198). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.099 for input, $0.495 for output).
At an average human reading speed of 250 words per minute, 10,000 words takes approximately 40 minutes to read. In contrast, Claude 3 Opus can process or generate this text in seconds.