Key Point 1: Google officially launches flagship AI model Gemini 2.0 Pro Experimental and introduces Gemini 2.0 Flash Thinking model, enhancing its competitiveness in the AI field.
Key Point 2: Facing competition from Chinese AI startup DeepSeek and its low-cost, high-efficiency AI model, Google attempts to increase its market share by integrating the Gemini 2.0 Flash Thinking model into its Gemini application.
Key Point 3: Gemini 2.0 Pro, as the flagship model of the Gemini series, performs excellently in encoding and processing complex prompts, and possesses stronger world knowledge understanding and reasoning capabilities. Its 2 million token context window allows it to handle a large amount of text content.
Google Introduces Gemini 2.0 Series
In response to DeepSeek’s low-cost, high-efficiency trend, Google officially launched the flagship AI model Gemini 2.0 Pro Experimental on Wednesday, along with the release of the Gemini 2.0 Flash Thinking model. This move is seen as an important step for Google to actively respond to competition in the AI field and consolidate its market position.
Gemini 2.0 Pro: Upgraded encoding capability and expanded context window
Gemini 2.0 Pro is the successor of Gemini 1.5 Pro, which was launched by Google in February last year. Google claims that it is now the flagship model in the Gemini AI model series. The model excels in encoding and processing complex prompts and has better world knowledge understanding and reasoning capabilities than any previous model.
According to Tech Church, Gemini 2.0 Pro can even access tools like Google Search and execute code on behalf of users.
It is worth mentioning that Gemini 2.0 Pro has a context window of 2 million tokens, which means it can process approximately 1.5 million words (English vocabulary) in a single prompt. This capacity is enough for it to read all seven books in the “Harry Potter” series in a single prompt, with approximately 400,000 words of space remaining.
The Gemini 2.0 series models have been officially launched.
Image/Google
Facing DeepSeek! Gemini 2.0 Flash Thinking enters the battle
Both Google and DeepSeek released AI reasoning models in December last year, but DeepSeek’s R1 received more attention. DeepSeek’s model is on par with, or even surpasses, the leading AI models offered by American tech companies in terms of performance. Moreover, companies can use these models at a relatively low cost through DeepSeek’s API.
To cope with the competition from DeepSeek, Google is trying to make the Gemini 2.0 Flash Thinking model more visible through the Gemini application. Google hopes to maintain its leading position in the highly competitive AI market with the launch of Gemini 2.0 Pro and Gemini 2.0 Flash Thinking.
Comparison of Gemini 2.0 series models
Gemini 2.0 Flash:
The main model in the Gemini series, suitable for daily tasks. It has significantly improved quality compared to 1.5 Flash, and has lower latency compared to 1.5 Pro while slightly improving quality.
Key features:
Equipped with a multi-modal real-time API, supporting low-latency bi-directional voice and video interactions. It outperforms Gemini 1.5 Pro in most quality benchmark tests. Improvements have been made in multi-modal understanding, encoding, following complex instructions, and function calls, supporting a better user experience. It also adds built-in image generation and controllable text-to-speech functionality, enabling image editing, localized artwork creation, and expressive storytelling.
Suitable scenarios:
Suitable for daily applications that require quick responses and high-quality outputs, such as real-time translation and video recognition.
Gemini 2.0 Flash-Lite:
It is the fastest and most cost-effective version of the Flash models, suitable for scenarios that require a balance between speed and cost.
Key features:
The quality is better than 1.5 Flash at the same price and speed. It has multi-modal input and text output capabilities, with a 1M token input context window and an 8k token output context window. However, it does not include the multi-modal output generation, multi-modal real-time API integration, thinking mode, and built-in tool usage features of Gemini 2.0 Flash.
Suitable scenarios:
Suitable for large-scale text output applications, such as generating titles for a large number of photos.
Gemini 2.0 Pro:
The model with the strongest encoding capability and world knowledge in the Gemini series, with a 2M long context window, suitable for scenarios that require processing a large amount of information and complex encoding tasks.
Key features:
Performs excellently in encoding and processing complex prompts, with stronger understanding and reasoning capabilities for world knowledge. It has a large context window of 2 million tokens, enabling comprehensive analysis and understanding of a large amount of information. It has tool invocation capabilities, such as Google Search.
Suitable scenarios:
Suitable for scenarios that require powerful encoding capability and handling complex problems, such as converting Python code to Java code. Researchers can also use Gemini 2.0 Pro to quickly read and understand a large amount of academic literature and automatically generate literature reviews, saving a significant amount of time and effort.
Further reading: Not just DeepSeek, but numerous potential AI companies in China, a list of 5 major ones
Source: TechChurch, Google
This article was initially generated by AI and revised/edited by Li Xiantai.