Processing or generating 1,000,000 words (approximately 1,333,000 tokens) with Qwen3 VL 235B Thinking (OpenRouter) ranges from $0.1333 (cached input) to $5.332 (full generation).
Quick answer
For 1,000,000 words, Qwen3 VL 235B Thinking (OpenRouter) processes approximately 1,333,000 tokens. That costs $0.5332 as uncached input, $0.1333 with the modeled cache discount, or $5.332 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 1,000,000 words as prompt context, documentation, or background knowledge.
Qwen3 VL 235B Thinking (OpenRouter) drafts a complete 1,000,000 words article, chapter, or code module.
800,000 words input prompt + 200,000 words output reply.
| Model | Provider | Input Cost (1,000,000 words) | Cached Input Cost | Output Cost (1,000,000 words) | Context Limit |
|---|---|---|---|---|---|
| Qwen3 VL 235B Thinking (OpenRouter) (Current) | qwen | $0.5332 | $0.1333 | $5.332 | 131,072 |
| GPT-5.6 Sol | openai | $6.40 | $0.64 | $38.40 | 1,050,000 |
| GPT-5.6 Cyber | openai | $16.00 | $1.60 | $96.00 | 1,050,000 |
| GPT-5.5 Standard | openai | $6.40 | $0.64 | $38.40 | 512,000 |
| GPT-5.5 Pro | openai | $38.40 | $3.84 | $230.40 | 512,000 |
| o3-pro (Frontier Reasoning) | openai | $25.60 | $2.56 | $102.40 | 1,000,000 |
For Qwen3 VL 235B Thinking (OpenRouter) (qwen_bpe tokenizer), 1,000,000 words is approximately 1,333,000 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 1,000,000 words as input costs $0.5332 (or $0.1333 with prompt caching). Generating 1,000,000 words as output costs $5.332. 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 $0.1333). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.2666 for input, $2.666 for output).
At an average human reading speed of 250 words per minute, 1,000,000 words takes approximately 4000 minutes to read. In contrast, Qwen3 VL 235B Thinking (OpenRouter) can process or generate this text in seconds.