Gemini 2.5 Pro: pricing, context and performance

What you need to know

Released on June 17, 2025, Gemini 2.5 Pro is one of the 14 Google DeepMind models tracked on this site. Its weights are not published, so it only runs remotely, through the Google DeepMind API or partner hosts (32 listed on models.dev). It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money. That makes it more than a year old: successors may have shipped since.

We file it under mid-range models (34 models in this category on the site).

Benchmark results

According to results published by Epoch AI (checked on October 22, 2026), Gemini 2.5 Pro has a capability index of 57 out of 100, computed on 5 benchmarks from our basket.

It is not among the top 30 of the weekly ranking.

• GPQA Diamond (PhD-level science questions): 85.3% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 84.7% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 24.6% — the best tracked model, GPT-6 Astra, reaches 93.7%
• SWE-bench Verified (fixing real software bugs): 57.6% — the best tracked model, Claude Opus 4.7, reaches 83.5%

Context and capabilities

Its context window reaches 1,048,576 tokens, roughly 1,573 pages of text at 500 words per page: enough to load a whole book or a mid-sized codebase. A single answer can run to 65,536 tokens.

It accepts as input: text, image, audio, video and PDF. Its knowledge stops at January 2025: beyond that, it needs web search or your documents.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

What it costs

Gemini 2.5 Pro costs $1.25 per million input tokens and $10 per million output tokens (developer's price, checked on October 22, 2026).

In practice, an agent task that reads 20,000 tokens and writes 2,000 costs about $0.045, or $45 for 1,000 such tasks.

That is 2.3 times the median output price of mid-range models ($4.38).

Tokens read back from cache cost $0.13 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

When to choose it

Given its category, Gemini 2.5 Pro is mainly aimed at a balance between quality and cost, for everyday uses that do not justify a frontier model.

Its very large context window makes it worth considering for analysing large sets of documents in a single request.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Comparable models

In the same category, the models closest to Gemini 2.5 Pro are:

• Qwen3 Max (Alibaba Cloud (Qwen), index 55.4)
• Gemini 3.5 Flash Lite (Google DeepMind, index 53.9)
• Claude Sonnet 4.6 (Anthropic, index 67.6)
• GPT-5.4 mini (OpenAI, index 68.4)