Gemini 3 Pro: It was worth the wait!!!

Based on the creator’s testing and benchmarks, Gemini 3 Pro demonstrates significant improvements over its predecessor, Gemini 2.5 Pro. Here is how they compare:

Performance and Efficiency (7:32 – 9:36): Gemini 3 Pro is notably faster than Gemini 2.5 Pro. In coding tasks, the new model generates more concise, higher-quality output using significantly fewer tokens (e.g., 3,500 tokens vs. 6,000 for the same task).
UI/UX Capabilities (9:36 – 10:22): The creator notes that Gemini 3 Pro produces user interfaces that feel more professional and less “AI-generated” compared to previous models. It excels at complex visual tasks, such as creating temporally consistent animations (like a crowd forming text) that Gemini 2.5 Pro could not handle effectively.
Benchmarks (1:39 – 2:01, 19:46 – 21:28):
- Gemini 3 Pro is the first model to cross the 1500 score on the LM Arena leaderboard.
- It achieves a score of 1487 on the WebDev Arena.
- The model shows high performance in advanced reasoning benchmarks, such as 37.5% on the Humanities Last Exam (outperforming GPT-5 Pro at 31.64%) and 92% on GPQA.

The wait for Gemini 3 Pro (and the recent 3.1 Pro upgrade) really did pay off. It feels like the first time “Agentic AI” has actually moved from a marketing buzzword to something we can use for heavy-duty work.

The leap from the 2.5 series to 3.1 Pro is massive, especially for complex logic or coding. Here are the three things that are absolutely crushing it right now:

1. The “ARC-AGI-2” Breakthrough

Seeing Gemini 3.1 Pro hit a 77.1% verified score on ARC-AGI-2 is the real headline. For context, that’s more than double the reasoning performance of the previous version. It’s no longer just predicting the next word; it’s actually solving novel logic puzzles it hasn’t seen in its training data.

2. Expanded “Agentic” Output

One of the biggest frustrations with older models was the “output ceiling”—where you’d ask for a complex app and it would just stop halfway through.

1M+ Input Context: Still the king of long-range memory.
64k Output Tokens: You can now generate entire multi-module codebases or 50-page technical reports in a single go without the model “forgetting” the start by the time it reaches the end.

3. The “Medium” Thinking Gear

The new Three-Tier Thinking system (Low, Medium, High) is a game-changer for workflow efficiency.

You can use Medium for things like “Vibe Coding” or UI layouts to get deep reasoning without the high latency of a full “High” reasoning cycle.
It makes the model feel much more like a tool you can tune depending on whether you’re brainstorming or doing PhD-level scientific synthesis (where it’s currently leading with a 94.3% on GPQA Diamond).

1. Video What is Vibe Coding?

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3. How to Vibe Code a Website

4. Visualizing World Models with Project Genie | Vibe Coding with Gemini

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12. Vibe Coding with Gemini 3 in Google AI Studio