Processing or generating 1,000 words (approximately 1,333 tokens) with Qwen 2.5 Max ranges from $0.000213 (cached input) to $0.008531 (full generation).
You send 1,000 words as prompt context, documentation, or background knowledge.
Qwen 2.5 Max drafts a complete 1,000 words article, chapter, or code module.
800 words input prompt + 200 words output reply.
| Model | Provider | Input Cost (1,000 words) | Cached Input Cost | Output Cost (1,000 words) | Context Limit |
|---|---|---|---|---|---|
| Qwen 2.5 Max (Current) | qwen | $0.002133 | $0.000213 | $0.008531 | 32,768 |
| GPT-5.6 Sol | openai | $0.0064 | $0.00064 | $0.0384 | 1,050,000 |
| GPT-5.6 Cyber | openai | $0.016 | $0.0016 | $0.096 | 1,050,000 |
| GPT-5.5 Standard | openai | $0.0064 | $0.00064 | $0.0384 | 512,000 |
| GPT-5.5 Pro | openai | $0.0384 | $0.00384 | $0.2304 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $0.0256 | $0.00256 | $0.1024 | 1,000,000 |
For Qwen 2.5 Max (qwen_bpe tokenizer), 1,000 words is approximately 1,333 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 1,000 words as input costs $0.002133 (or $0.000213 with prompt caching). Generating 1,000 words as output costs $0.008531. 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 $0.000213). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.001066 for input, $0.004266 for output).
At an average human reading speed of 250 words per minute, 1,000 words takes approximately 4 minutes to read. In contrast, Qwen 2.5 Max can process or generate this text in seconds.