Processing or generating 2,500 words (approximately 3,333 tokens) with Cohere Command R ranges from $0.000125 (cached input) to $0.002 (full generation).
You send 2,500 words as prompt context, documentation, or background knowledge.
Cohere Command R drafts a complete 2,500 words article, chapter, or code module.
2,000 words input prompt + 500 words output reply.
| Model | Provider | Input Cost (2,500 words) | Cached Input Cost | Output Cost (2,500 words) | Context Limit |
|---|---|---|---|---|---|
| Cohere Command R (Current) | cohere | $0.0005 | $0.000125 | $0.002 | 128,000 |
| GPT-5.6 Luna | openai | $0.00064 | $0.000064 | $0.00384 | 1,050,000 |
| GPT-5.4 mini | openai | $0.0024 | $0.00024 | $0.0144 | 256,000 |
| GPT-5.4 nano | openai | $0.00064 | $0.000064 | $0.004 | 128,000 |
| GPT-4o mini | openai | $0.00048 | $0.00024 | $0.00192 | 128,000 |
| Claude Haiku 4.5 | anthropic | $0.0033 | $0.00033 | $0.0165 | 1,000,000 |
For Cohere Command R (cohere_bpe tokenizer), 2,500 words is approximately 3,333 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 2,500 words as input costs $0.0005 (or $0.000125 with prompt caching). Generating 2,500 words as output costs $0.002. 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 $0.000125). For non-urgent asynchronous batch processing, 24-hour batch queues provide a flat 50% discount across all tokens (costing $0.00025 for input, $0.001 for output).
At an average human reading speed of 250 words per minute, 2,500 words takes approximately 10 minutes to read. In contrast, Cohere Command R can process or generate this text in seconds.