Processing or generating 1,000,000 words (approximately 1,333,000 tokens) with Mistral Large 3 ranges from $0.0667 (cached input) to $1.999 (full generation).
Quick answer
For 1,000,000 words, Mistral Large 3 processes approximately 1,333,000 tokens. That costs $0.6665 as uncached input, $0.0667 with the modeled cache discount, or $1.999 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.
Mistral Large 3 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 |
|---|---|---|---|---|---|
| Mistral Large 3 (Current) | mistral | $0.6665 | $0.0667 | $1.999 | 1,000,000 |
| 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 Mistral Large 3 (mistral_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 $0.6665 (or $0.0667 with prompt caching). Generating 1,000,000 words as output costs $1.999. 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 $0.0667). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.3333 for input, $0.9997 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, Mistral Large 3 can process or generate this text in seconds.