Google has been on a tear in the past weeks, shipping a new open-weight model, an image generation model, a free AI coding assistant, and a slew of useful features for its Gemini app. And just yesterday, it released Gemini 2.5 Pro, the latest version of its flagship large language model (LLM).
Gemini 2.5 Pro brings Google close to the edge of the tight LLM race (though at this point, it is really hard to tell the best model—it’s all about “vibe checks” these days). Gemini 2.5 Pro is not without its quirks, but with Google’s massive distribution channels and developer infrastructure, it can give it a boost in the AI race.
What is Gemini 2.5 Pro
Gemini 2.5 Pro is a reasoning model (or “thinking model” as Google says in its blog post), which means instead of directly responding to prompts, it first generates “thought” tokens that meticulously break down the problem and gradually build the solution. It is the equivalent of OpenAI o3, DeepSeek R1, and Grok 3 Reasoning.
Interestingly, there is no non-reasoning version of Gemini 2.5 Pro. This is a bit odd since reasoning increases inference costs and slows down the model’s response time, extending the “time to first token,” and deteriorating the user experience.
There is not a lot of information in Google’s blog about the architecture or training data of Gemini 2.5 Pro aside that “with Gemini 2.5, we’ve achieved a new level of performance by combining a significantly enhanced base model with improved post-training.” The blog post mentions that Google had been experimenting with chain-of-thought (CoT) and reinforcement learning (RL) with Gemini 2.0 Flash Thinking, their previous reasoning model.
Also, unlike previous versions of Gemini, Google did not release the smaller Flash version of the model before the Pro version. This suggests that Gemini 2.5 Pro is Gemini 2.0 Pro trained on RL and other post-training techniques.
One of the outstanding features of Gemini 2.5 Pro is its one-million-token context window, making it suitable for reasoning over very long documents and code bases. (Other leading reasoning models have 64,000–200,000-token context windows.)
According to Google’s experiments, Gemini 2.5 Pro is neck and neck with other models on major benchmarks, including reasoning and knowledge (Humanity’s Last Exam), science reasoning (GPQA), mathematics (AIME), multi-modal problem-solving (MMMU), and coding (SWE-Bench and Aider Polyglot). This makes it a well-rounded model for a wide range of tasks. Notably, Google outperforms other leading models in long-context reasoning (MRCR).
Gemini 2.5 Pro has also received the approval of independent reviewers, including clinching the top spot on LMArena, a platform for blind tests on how different models perform on the same prompt, and getting top scores on several benchmarks in Scale AI’s SEAL leaderboard.
Gemini 2.5 Pro is currently in preview mode. You can access it for free in Google AI Studio with limited access. It is also available to Gemini Advanced users ($20 per month) and will soon be available on Google’s Vertex AI platform.
What does Gemini 2.5 Pro mean for Google’s AI strategy?
Many thought Google had lost the AI game to OpenAI and Anthropic. But let’s not forget that 1) the transformer architecture, which is the backbone of modern language models, was invented at Google, and 2) Google still has one of the brightest teams of AI scientists and engineers in DeepMind. With Gemini 2.5 Pro and other recent releases, Google has shown that it has fully caught up with the state-of-the-art in AI.
However, the bigger question is what is Google’s bigger AI strategy. The Gemini app is basically a clone of ChatGPT. And although I really like the features and experience of the Gemini app, I’m not sure if it will be Google’s best product. In this field, OpenAI has the brand advantage and greater traction with hundreds of millions of weekly active users. And Gemini cannibalizes Google’s main revenue generator, which is its search engine. Unless Google delivers a product that is 10x better than ChatGPT and subsidizes it through its huge cash flows to kill the competitors, I can’t see how Google will be able to outcompete OpenAI.
The greater opportunity for Google will be integrating models such as Gemini 2.5 Pro into its distribution channels, including Search, Gmail, Docs, Sheets, and other applications. With its ability to add relevant data points into Gemini 2.5 Pro’s massive context window, Google can become the king of AI integration. Google’s developer tools and infrastructure, including the super-useful AI Studio, can also turn it into the winner of the AI development wars, giving developers a very smooth on-ramp to build with LLMs and integrate them into their applications. Gemini 2.0 Flash already has the pricing advantage over other model APIs. We will have to see the pricing model for Gemini 2.5 Pro to see how it stands against competitors in capturing the developer market for large reasoning models (LRMs).