Gemini 2.5 Pro is Google’s most expensive AI model yet

On Friday, Google released API pricing for Gemini 2.5 Pro, an AI reasoning model with industry-leading performance on several benchmarks measuring coding, reasoning, and math.

For prompts up to 200,000 tokens, Gemini 2.5 Pro costs $1.25 per million input tokens (roughly 750,000 words, longer than the entire “Lord of The Rings” series) and $10 per million output tokens. For prompts greater than 200,000 tokens (which most of Google’s competitors don’t support), Gemini 2.5 Pro costs $2.50 per million input tokens and $15 per million output tokens.

That pricing makes Gemini 2.5 Pro more expensive for developers than any other AI model currently offered by Google, including Gemini 2.0 Flash ($0.10/million input tokens, $0.40/million output tokens). It also makes Gemini 2.5 Pro more expensive than several other frontier AI models, such as OpenAI’s o3-mini ($1.10/million input tokens, $4.40/million output tokens) and DeepSeek’s R1 ($0.55/million input tokens, $2.19/million output tokens).

To be fair, Gemini 2.5 Pro, which is available for free with strict rate limits, comes in cheaper than some other highly competitive models, including Anthropic’s Claude 3.7 Sonnet ($3/million input tokens, $15/million output tokens) and OpenAI’s GPT-4.5 ($75/million input tokens, $150/million output tokens). The tech industry’s initial reaction has been largely positive, with developers praising what they perceive to be sensible rates.

But broadly speaking, there seems to be some upward pressure on pricing for flagship models. The cost of recent top-of-the-line releases from labs like Google, OpenAI, and Anthropic has been going up, not down. See, for example, OpenAI’s recently launched o1-pro, which is the company’s most expensive API offering yet at $150/million input tokens and $600/million output tokens.

It could be that high demand and computing costs are driving the trend. According to Google CEO Sundar Pichai, Gemini 2.5 Pro is the company’s most in-demand AI model among developers, leading to an 80% increase in usage in Google’s AI Studio platform and the Gemini API this month alone.