Qwen2 72b BEATS LLaMA3 70b - Fully Tested (0.5b not good)

The video compares the performance of the Quen 2 model, available in both 72 billion and 0.5 billion parameter versions, with the Llama 3 model. The Quen 2 model, particularly the 72 billion parameter version, demonstrates superior capabilities in handling various prompts and tasks, outperforming the Llama 3 model and showcasing advancements in AI models for natural language processing.

In this video, a comparison is made between the newly released Quen 2 model by The Alibaba Group and the Llama 3 model. The Quen 2 model is tested in two variations: a 72 billion parameter version and a 0.5 billion parameter version, aiming to showcase both quality and speed. The Quen 2 model offers pre-trained and instruction-tuned models in various sizes, with extended context length support for the larger versions.

The performance evaluation of Quen 2, particularly the 72 billion parameter version, shows that it outperforms Llama 3 and other models across various evaluations. In the testing process, different prompts are given to the models, such as coding tasks, logic and reasoning questions, and word-related queries. The results vary between the two models, with the larger Quen 2 model generally providing more accurate and detailed responses compared to the smaller version.

The testing reveals that the smaller model struggles with complex questions, often failing to produce accurate responses or complete tasks correctly. In contrast, the larger Quen 2 model demonstrates better understanding and reasoning capabilities, yielding more precise and insightful answers. The models’ performance is assessed based on their ability to handle a range of prompts and tasks, showcasing the differences in their capabilities.

While the smaller model shows limitations in handling certain types of queries, such as logic problems and open-ended questions, the larger Quen 2 model excels in providing coherent explanations and accurate solutions. The video highlights the importance of model size and parameters in determining the quality of responses and overall performance. The Quen 2 model, particularly the 72 billion parameter version, emerges as a powerful and versatile tool for a wide range of natural language processing tasks.

Overall, the comparison between the Quen 2 model and Llama 3 demonstrates the advancements in AI models and their capabilities. The video showcases the impact of model size on performance and the potential applications of these models in various fields. The Quen 2 model stands out for its superior performance and accuracy, especially in handling complex queries and tasks. The evolution of AI models like Quen 2 highlights the continuous progress in natural language processing and the potential for further advancements in the future.