Google Reshapes AI Search Experience, Ushering in a New Era of Efficient Intelligence

On December 18th, the AI industry witnessed a major year-end breakthrough — Google unexpectedly officially launched the Gemini 3 Flash model. This lightweight large model focusing on "ultra-fast response + high-level intelligence" not only directly replaces Gemini 2.5 Flash as the default model for Gemini applications and Google Search's AI mode, but also breaks the inherent contradiction between intelligence and efficiency with a response speed as smooth as traditional search. It is expected to completely reshape the current user experience of AI search and point out a new direction for the industry's development.

For a long time, there has been an "impossible trinity" in the field of AI models: high intelligence, low cost, and fast response. Lightweight models often compromise intelligence in pursuit of speed, while flagship models are difficult to popularize due to cost and latency constraints. The advent of Gemini 3 Flash has precisely broken this industry dilemma. Third-party benchmark test data shows that its running speed is three times faster than the previous-generation Gemini 2.5 Pro, and the response time for daily interactions is basically controlled within 1 second, perfectly fulfilling the commitment of "traditional search-level fluency". When users upload a short video for tactical analysis, hand-draw a sketch for intelligent feedback, or query daily information, they can get an almost lag-free experience.

What is even more amazing is the leapfrog improvement in its intelligence level. In the authoritative benchmark test SWE-bench Verified for evaluating coding agent capabilities, Gemini 3 Flash scored as high as 78%, which not only far surpasses the previous-generation model, but also outperforms Google's own flagship model Gemini 3 Pro. In the multimodal reasoning benchmark MMMU Pro, its high score of 81.2% ranks among the top in the industry, and it even achieved an excellent score of 90.4% in the doctoral-level reasoning test GPQA Diamond. Even in the cross-domain expert-level test Humanity’s Last Exam, it still achieved a score of 33.7% without tool usage, far exceeding Gemini 2.5 Flash's 11%, and even approaching GPT-5.2's 34.5%.

The core innovation of this release lies in the reshaping of the AI search experience. As the default model for Google Search's AI mode, Gemini 3 Flash has achieved a perfect integration of in-depth reasoning and real-time response. When users query the "2025 World Cup schedule", they will directly get a visual calendar with dates and opposing teams, which can be added to the mobile phone calendar with one click; when searching for "cake baking tutorials", it will present graphic steps and common problem prompts, which is much more intuitive than traditional text lists. This upgrade from "information matching" to "real-time answering" makes high-level reasoning a standardized service for public retrieval, completely changing the core logic of AI search.

The cost-performance advantage is even more the "killer feature" of Gemini 3 Flash. Its pricing is as low as $0.50 per million input tokens and $3 per million output tokens, which is only a quarter of that of Gemini 3 Pro. At the same time, the average token consumption for processing thinking tasks is 30% less than that of Gemini 2.5 Pro. With context caching technology, the cost can be saved by 90% in some scenarios. This advantage not only allows ordinary users to enjoy cutting-edge AI services for free, but also greatly reduces the deployment threshold for developers and enterprises. At present, JetBrains, Figma, Bridgewater Associates and other companies have taken the lead in accessing it, reporting that it performs outstandingly in reasoning speed and cost control, while the quality is close to that of flagship models.

From the perspective of the industry pattern, the launch of Gemini 3 Flash marks that AI competition has shifted from the competition of parameter scale to the competition of intelligent output per unit of computing power. Through the product line layout of "flagship-level Pro + popular Flash", Google has quickly seized the entrance of daily AI applications. The monthly active users of the Gemini App have exceeded 650 million, and the switch of the default model will accumulate a large amount of interaction data to feed back model iteration. Facing competition from OpenAI, Google's "fast, accurate and ruthless" strategy not only strengthens its ecological advantages, but also accelerates the arrival of the agent era.

Of course, Gemini 3 Flash is not perfect. It is still inferior to flagship models in scenarios such as complex architecture design and advanced math problem solving, and its multimodal understanding in the Chinese context still needs optimization. But it is undeniable that it has removed the last barrier between speed and intelligence. With its popularization around the world, AI will truly integrate into daily high-frequency scenarios, transforming from a professional tool into an intelligent assistant available to everyone, and opening a new era of efficient intelligence.