Gemini 3.5 Pro Leak: Is Google Falling Behind?

Google's upcoming flagship, Gemini 3.5 Pro, is facing early skepticism ahead of its official release. According to Geeky Gadgets, which cited the YouTube analysis channel Universe of AI, preliminary tests of a leaked checkpoint indicate that the model lags behind Anthropic's Fable 5 and OpenAI's GPT-5.6 in advanced reasoning, coding, and long-horizon task execution.

However, it remains critical to note that Gemini 3.5 Pro is still unreleased, and the leaked performance metrics constitute unverified rumors that Google has not confirmed. Nonetheless, from the critical reception following last month's I/O to this recent leak, a series of negative signals has deepened doubts about Google's standing among frontier models.

Key Weaknesses Identified: Reasoning, Coding, and Pricing

The leaked checkpoint analysis highlights three primary areas of concern. First, in advanced reasoning, Fable 5 and GPT-5.6 reportedly maintain a distinct advantage in managing complex, multi-step workflows. Second, in coding, limitations in bidirectional processing and code infilling cast doubt on the model's utility for developers.

Third, pricing represents a significant hurdle, as Gemini 3.5 Pro is rumored to cost more than its direct competitors. A higher price point for a model that underperforms in core areas could hinder adoption, particularly as Chinese open-source models rapidly improve in natural language processing and multimodal understanding to capture the budget segment.

Industry and developer sentiment has reacted coolly to these reports. Following the leak, social media posts arguing that Google has fallen behind multiplied on X, reflecting growing fatigue over recurring negative reports surrounding the Gemini lineup.

Strengths in Vision and the Diffusion Gemma Experiment

Despite the critical findings, the leak also highlights notable areas of improvement. Visual generation and SVG rendering have reportedly made significant strides, while multimodal understanding—integrating text and image processing—has become more precise. These capabilities could prove valuable in design and education. Additionally, safety filters have been strengthened, offering enterprise appeal at the expense of operational flexibility.

The leak also references Diffusion Gemma, an experimental local model designed for on-device execution. By processing tokens in 256-token blocks, Diffusion Gemma reportedly generates text up to four times faster than standard autoregressive models, albeit at the cost of output quality. Designed to run on consumer GPUs, Diffusion Gemma could serve as a useful tool for developers exploring local deployment.

Official Launches to Test Frontier Capabilities

Beyond experimental models, the primary focus remains on Google's flagship tiers. To date, the company has only officially released Gemini 3.5 Flash, which debuted at Google I/O in May. According to its official model card, Flash scores 76.2% on Terminal-Bench 2.1 and 83.6% on MCP Atlas, outperforming the previous-generation Pro tier in agentic and coding tasks. However, it still lags behind frontier models on complex reasoning benchmarks.

Gemini 3.5 Pro was designed to close this reasoning gap, which explains why the leak has caused concern. If the rumors are accurate, Google risks launching a more expensive model that still underperforms in reasoning. Conversely, if the official release is substantially improved over the leaked checkpoint, the controversy will likely be dismissed as market overreaction to unverified data.

A definitive assessment is imminent. Gemini 3.5 Pro is expected to launch this month, concurrent with anticipated releases from OpenAI and Anthropic. Google's performance in the upcoming frontier model race will determine whether this leak was an accurate preview or merely premature noise.