AI

LLM Pricing Comparator

Compare model pricing for input and output tokens across providers.

All tools

Usage estimate

Prices in USD per 1M tokens. Reference only; check provider docs for current rates.

Cost ranking

ModelProvider$/1M in$/1M outEstimated cost
GPT-4o miniOpenAI$0.15$0.60$0.0270
DeepSeek V3DeepSeek$0.27$1.10$0.0490
GPT-5 miniOpenAI$0.25$1.25$0.0500
Gemini 2.5 FlashGoogle$0.30$2.50$0.0800
Llama 3.3 70BMeta (Together)$0.88$0.88$0.1056
Claude Haiku 4.5Anthropic$1.00$5.00$0.2000
Mistral Large 2Mistral$2.00$6.00$0.3200
Gemini 2.5 ProGoogle$1.25$10.00$0.3250
GPT-4oOpenAI$2.50$10.00$0.4500
Claude Sonnet 4.6Anthropic$3.00$15.00$0.6000
GPT-5OpenAI$10.00$30.00$1.6000
Claude Opus 4.7Anthropic$15.00$75.00$3.0000

Frequently asked questions

Why is output more expensive than input?
Generating tokens is autoregressive and uses far more compute per token than reading the prompt, which is processed in parallel. Output prices typically run 3-5x the input rate.
How is pricing usually quoted?
Per million tokens, split into input and output rates, sometimes with extra tiers for cached input, batch jobs, or extended context. Multiply rate by tokens then divide by one million.
Do cheaper models always cost less overall?
Not necessarily. A weaker model often needs more retries, longer prompts, or larger few-shot examples to hit the same quality, which can erase the per-token savings.