Introduction to Gemini 2.5 Pro Experimental
Just a few months after releasing its first Gemini 2.0 AI models, Google is upgrading again. The company says the new Gemini 2.5 Pro Experimental is its "most intelligent" model yet, offering a massive context window, multimodality, and reasoning capabilities. Google points to a raft of benchmarks that show the new Gemini clobbering other large language models (LLMs), and our testing seems to back that up—Gemini 2.5 Pro is one of the most impressive generative AI models we’ve seen.
What’s New in Gemini 2.5 Pro Experimental
Gemini 2.5, like all Google’s models going forward, has reasoning built in. The AI essentially fact-checks itself along the way to generating an output. We like to call this "simulated reasoning," as there’s no evidence that this process is akin to human reasoning. However, it can go a long way to improving LLM outputs. Google specifically cites the model’s "agentic" coding capabilities as a beneficiary of this process. Gemini 2.5 Pro Experimental can, for example, generate a full working video game from a single prompt. We’ve tested this, and it works with the publicly available version of the model.
Video Game Generation Example
Gemini 2.5 Pro builds a game in one step. This is demonstrated in a video where the model generates a fully functional game based on a single prompt.
Technical Upsides of Gemini 2.5 Pro
Google says a lot of things about Gemini 2.5 Pro; it’s smarter, it’s context-aware, it thinks—but it’s hard to quantify what constitutes improvement in generative AI bots. There are some clear technical upsides, though. Gemini 2.5 Pro comes with a 1 million token context window, which is common for the big Gemini models but massive compared to competing models like OpenAI GPT or Anthropic Claude. You could feed multiple very long books to Gemini 2.5 Pro in a single prompt, and the output maxes out at 64,000 tokens. That’s the same as Flash 2.0, but it’s still objectively a lot of tokens compared to other LLMs.
Benchmark Performance
Naturally, Google has run Gemini 2.5 Experimental through a battery of benchmarks, in which it scores a bit higher than other AI systems. For example, it squeaks past OpenAI’s o3-mini in GPQA and AIME 2025, which measure how well the AI answers complex questions about science and math, respectively. It also set a new record in the Humanity’s Last Exam benchmark, which consists of 3,000 questions curated by domain experts. Google’s new AI managed a score of 18.8 percent to OpenAI’s 14 percent.
Conclusion
In conclusion, Gemini 2.5 Pro Experimental is a significant upgrade to Google’s AI models. With its massive context window, multimodality, and reasoning capabilities, it outperforms other large language models in various benchmarks. The ability to generate a full working video game from a single prompt is a notable example of its capabilities. As AI technology continues to evolve, we can expect to see even more impressive models in the future.
FAQs
Q: What is Gemini 2.5 Pro Experimental?
A: Gemini 2.5 Pro Experimental is a new AI model developed by Google, offering a massive context window, multimodality, and reasoning capabilities.
Q: What is the context window of Gemini 2.5 Pro?
A: The context window of Gemini 2.5 Pro is 1 million tokens, which is massive compared to competing models.
Q: Can Gemini 2.5 Pro generate video games?
A: Yes, Gemini 2.5 Pro Experimental can generate a full working video game from a single prompt.
Q: How does Gemini 2.5 Pro perform in benchmarks?
A: Gemini 2.5 Pro scores higher than other AI systems in various benchmarks, including GPQA, AIME 2025, and Humanity’s Last Exam.
