LLM Costs per MTok
Provider | Model | Input ($/MTok) | Output ($/MTok) |
Replicate / Meta | llama-3-8b | $0.05 | $0.25 |
Together / Meta | llama-3-8b | $0.2 | $0.2 |
Anthropic | claude-3 haiku | $0.25 | $1.25 |
OpenAI | gpt-3.5-turbo | $0.5 | $1.5 |
Together / Mistral | mixtral-8x7b | $0.6 | $0.6 |
Anthropic | claude-2-instant | $0.8 | $2.4 |
Together / Meta | llama-3-70b | $0.9 | $0.9 |
OpenAI | finetuned gpt-3.5-turbo | $3 | $6 |
Anthropic | claude-3 sonnet | $3 | $15 |
Anthropic | claude-2 | $8 | $24 |
OpenAI | gpt-4-turbo | $10 | $30 |
Anthropic | claude-3 opus | $15 | $75 |
OpenAI | gpt-4-8k | $30 | $60 |
OpenAI | gpt-4-32k | $60 | $120 |
Last updated: Apr 18 2024
FAQ
Q: What is a MTok?
A: 1 million tokens
Q: Are tokens the same across providers? Does this comparison make sense?
A: No, tokens are different, but they should be close enough.
- Comparing Anthropic vs OpenAI, Anthropic has no public tokenizer, but claims their tokens are ~3.5 English chars per token. OpenAI claims their tokens are ~4 English chars per token. So perhaps Anthropic prices in the above table are an underestimate, and should be increased by 14%.
- Comparing Mixtral vs OpenAI - the Mixtral vocabulary size is 32000 vs OpenAI’s 100,256. This might imply that Mixtral costs too are underestimated, but I’m not entirely sure how big the difference is.