Processing or generating 1,000,000 words (approximately 1,333,000 tokens) with Fireworks AI — DeepSeek R1 ranges from $0.1833 (cached input) to $2.919 (full generation).
You send 1,000,000 words as prompt context, documentation, or background knowledge.
Fireworks AI — DeepSeek R1 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 |
|---|---|---|---|---|---|
| Fireworks AI — DeepSeek R1 (Current) | fireworks | $0.7332 | $0.1833 | $2.919 | 128,000 |
| GPT-5.6 Terra | openai | $2.56 | $0.256 | $15.36 | 1,050,000 |
| GPT-5.4 Workhorse | openai | $3.20 | $0.32 | $19.20 | 256,000 |
| o3-mini | openai | $1.408 | $0.704 | $5.632 | 200,000 |
| o4-mini | openai | $1.408 | $0.352 | $5.632 | 256,000 |
| o1-mini | openai | $1.408 | $0.704 | $5.632 | 128,000 |
For Fireworks AI — DeepSeek R1 (deepseek_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 $0.7332 (or $0.1833 with prompt caching). Generating 1,000,000 words as output costs $2.919. 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 $0.1833). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.3666 for input, $1.46 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, Fireworks AI — DeepSeek R1 can process or generate this text in seconds.