Cohere Token Counter
Cohere's Command models use a large-vocabulary BPE tokenizer built for multilingual enterprise text. TokenMath counts Cohere tokens with a calibrated estimate, typically within ±3%.
Universal AI Token Counter
Zero-latency, client-side BPE tokenization with real-time multi-model benchmarks.
Cohere Models: Context Windows & Token Prices
| Model | Context Window | Input / 1M | Output / 1M | Token Count Accuracy |
|---|---|---|---|---|
| Command A | 256k tokens | $2.5 | $10 | Calibrated Cohere Tokenizer (±3%) |
How Cohere Tokenization Works
Cohere models split text with the Cohere BPE tokenizer, a Byte-Pair Encoding (BPE) scheme with a ~256,000 tokens vocabulary. Common words map to one token, while rare words, identifiers and non-Latin scripts are split into several subword pieces. Read how BPE and SentencePiece tokenization work for the details.
- Command models are commonly used for RAG; retrieved documents usually dominate the input token count.
Once you know your token count, estimate a full monthly bill with the LLM cost calculator, or see every Cohere model price.
Cohere Token Counter FAQ
How do I count Cohere tokens?
Paste your prompt into the counter above with a Cohere model selected. TokenMath tokenizes the text in your browser and shows the token count, context window usage and input cost. Accuracy: Calibrated Cohere Tokenizer (±3%).
What tokenizer does Cohere use?
Cohere models are counted with the Cohere BPE tokenizer (Byte-Pair Encoding (BPE), ~256,000 tokens vocabulary). Cohere's Command models use a large-vocabulary BPE tokenizer built for multilingual enterprise text.
How many words is 1,000 Cohere tokens?
For typical English prose, 1,000 tokens is roughly 700–750 words. Code, JSON and non-English text use more tokens per word, so count the actual text when budgeting.
How much does Command A cost per token?
Command A costs $2.5 per 1M input tokens and $10 per 1M output tokens. That's $0.00250 per 1,000 input tokens.