Google rolls out Gemini 2.5 Pro, now free for all users

Google just gave us something new to talk about: an experimental version of its latest model, Gemini 2.5 Pro. This is the newest and what Google believes to be its most intelligent AI model yet. Plus, Google is now providing free access to this experimental version for all users, allowing more people to experience its newest AI capabilities firsthand. Let’s look closer at how Gemini 2.5 Pro works and why it’s worth paying attention to.

Gemini 2.5 Pro is Google’s most intelligent AI yet

So, what’s different here? Google’s Gemini 2.5 family introduces the idea of “thinking models”. The experimental Pro version is the first to use this approach, designed to better handle complex problems by pausing to “think” before responding. Essentially, it breaks tasks into smaller steps and uses logical reasoning to arrive at, hopefully, more accurate and well-considered answers.

Google believes this method improves performance across various tasks, and, moving forward, it’s a capability we’ll see in all future models in the Gemini 2.5 series.

Stronger reasoning and coding

Gemini 2.5 Pro Experimental shows strong results in reasoning tasks, achieving high scores on several standard AI benchmarks. Notably, it currently holds the top spot on the LMArena leaderboard – which basically means human testers preferred its output quality. It also achieved an impressive 18.8% on Humanity’s Last Exam without using external tools. That particular benchmark is tough, designed by experts to test advanced knowledge and reasoning, so scoring well there highlights the model’s sophisticated understanding.

Beyond reasoning, Google also put significant effort into improving coding capabilities compared to Gemini 2.0. This new model is quite skilled at generating code for web apps and tasks needing agent-like behavior (what they call agentic code).

It also shows better performance in transforming and editing existing code. We’ve seen demos where Gemini 2.5 Pro generated functional code for complex things like interactive 3D simulations, solving the Rubik’s cube, or making games from just one prompt — which could be a potentially very powerful tool for developers who want to work faster and try new creative approaches.

Processing large amounts of information

One of the most talked-about features is its massive 1 million token context window. To put this into perspective, a million tokens can roughly translate to around 750,000 words — more text than the entire “Lord of the Rings” trilogy! This huge capacity allows the model to process and understand really large amounts of information in one go, whether that’s long documents, big codebases, or even hours of audio or video.

Plus, Google plans to double this to 2 million tokens soon, which opens up even more possibilities for addressing complex problems that need insights from vast amounts of data.

Read also: Free ebook on Gemini Prompting Guide 101, with best practices on how to prompt Gemini.

Benchmarking Gemini 2.5 Pro against competitors

Google obviously isn’t the only one building large language models. How does Gemini 2.5 Pro compare to competitors in the space? Against models from other major players, it performs well and often shows very good results.

While benchmark results always need context, here’s a more detailed look at where Gemini 2.5 Pro stands based on specific tests:

1. Overall performance & benchmarks

• A key result is its score on Humanity’s Last Exam (18.8%) without using external tools — the best score recorded so far for this challenging reasoning test, surpassing models like o3-mini (14%) and DeepSeek R1 (8.6%).
• It also leads the LMArena leaderboard by a good margin — arena score 1443 — this benchmark reflects how much human testers prefer the quality and style of its responses.
• On math and science tests like GPQA and AIME 2025, Gemini 2.5 Pro reportedly leads without using test-time techniques that increase cost.
• It also shows strong performance on the widely used MMLU benchmark and scores very well on MRCR (Multi Round Coreference Resolution), a long-context evaluation.

2. Coding

• Google itself calls the improvement in coding over Gemini 2.0 a “big leap”.
• On SWE-Bench Verified, an industry standard for agentic code evaluations, Gemini 2.5 Pro scores 63.8% with a custom agent setup, outperforming o3-mini and DeepSeek’s R1, but underperforming Anthropic’s Claude 3.7 Sonnet (70.3%).
• On the Aider Polyglot coding benchmark, Gemini 2.5 Pro absolutely dominated, scoring 68.6% and outperforming top models from OpenAI, Anthropic, and DeepSeek.
• The model is capable of generating complex code, such as for interactive 3D simulations and video games, from single prompts

3. Context window

• Its standard 1 million token context window is remarkably large — enough to process roughly 750,000 words at once.
• The plan to increase this to 2 million tokens soon will make it even better at handling huge amounts of information, keeping it among the models with the largest context windows available.

4. Reasoning

• Gemini 2.5 Pro is explicitly described as a “thinking model” — the idea is that by reasoning through steps before answering, it can achieve better accuracy, especially on complex tasks.

Free access via Google AI Studio and Gemini app

Perhaps the best part for many readers is that Google has now made the experimental version of Gemini 2.5 Pro available to all users for free. Access used to be more limited, mainly for Gemini Advanced subscribers or via Google AI Studio.

Now, you can test its capabilities directly by accessing it through Google AI Studio or by selecting it as the model within the Gemini app. This wider access is great because it lets more people experiment, provide feedback, and maybe even generate new ideas. For businesses looking to build on this, Gemini 2.5 Pro is also planned to arrive on Vertex AI, Google Cloud’s machine learning platform, soon.

So, Google’s experimental Gemini 2.5 Pro is definitely an important update in the AI landscape. Better reasoning, strong coding skills, and that huge context window make it a very capable model. The fact that it’s now freely accessible is a great opportunity for anyone interested in AI, to see what it can do. It’s worth checking out via Google AI Studio or the Gemini app to understand where Google is heading with its AI technology.

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