Zamba 2 performance evaluation

In this thought-provoking video, Matthew Berman examines the performance of the new Llama-based model, Zamba 2, which claims to rival leading models like GPT-4 and Mistral in both speed and quality. He tests the model’s capabilities across various benchmarks, including generating code and solving logic problems, while highlighting its efficiency and open-source nature. Despite the model’s promising specifications, Matthew encounters several failures during the tests, leading to a critical evaluation of non-transformer models’ performance. He discusses the implications of these results for the future of AI and web scraping, urging viewers to consider the effectiveness of different models in real-world applications. The video concludes with reflections on the challenges of achieving high performance in AI models and invites viewers to share their thoughts on the findings.