In the video “Claude 3.5 Sonnet NEW is Really Good - Full Test,” the presenter evaluates the performance of the Claude 3.5 model by testing its coding abilities through the creation of Snake and Tetris games, where it successfully generates functional code despite some initial errors. The model also undergoes various logic and reasoning tests, performing well in some areas while struggling in others, ultimately receiving a positive overall assessment for its capabilities.
In the video titled “Claude 3.5 Sonnet NEW is Really Good - Full Test,” the presenter evaluates the performance of the newly released Claude 3.5 model across various coding and reasoning tasks. The video begins with a brief introduction, highlighting that Claude 3.5 has shown impressive results in benchmarks, particularly in coding. The presenter decides to test the model’s capabilities by creating two classic games: Snake and Tetris, using Python. The coding process is demonstrated, with the model successfully generating functional code for Snake, which performs well during gameplay.
Next, the presenter moves on to the Tetris game, where the model initially encounters an issue with the rotation of the pieces, causing the game to crash. However, after identifying the error, the presenter inputs the suggested fix from Claude 3.5, which resolves the issue, allowing the game to function correctly. Although the model did not get it right on the first attempt, the quick correction demonstrates its coding proficiency, earning a pass for this task.
The video then transitions to logic and reasoning tests, starting with a problem about envelope size restrictions. Here, Claude 3.5 fails to account for the possibility of rotating the envelope to fit within the size limits. This oversight results in a negative evaluation for this task. The presenter continues with various reasoning questions, including counting words in a response and solving riddles, where the model performs well in some instances but fails to provide accurate answers in others.
The evaluation also includes a visual recognition test, where the model is asked to describe an image of a llama and identify a person in a photo. While it successfully describes the llama, it struggles to identify the individual in the second image. Additionally, the model is tested on its ability to decode a QR code, which it cannot do. However, it excels in answering questions about a screenshot from an iPhone, accurately providing details about storage usage and identifying apps offloaded to the cloud.
In conclusion, the presenter expresses overall satisfaction with Claude 3.5’s performance, noting that it only encountered a few minor errors throughout the tests. The model’s ability to generate functional code and provide logical reasoning is commendable, despite some shortcomings in specific tasks. The video wraps up with an invitation for viewers to share their thoughts in the comments and encourages them to like and subscribe for more content.