GPT-4 vs. Claude 2 vs. Llama 2 - Comparing LLM Models VOL:1

We tested GPT-4, Claude 2, and Llama 2 on a complex language prompt to see how they compared. Read on for the results and insights into each model's strengths and weaknesses.

Artificial intelligence has advanced rapidly, with new large language models emerging that boast impressive language skills. But how well do they perform on tricky, nuanced language tasks?

We decided to test out three of the latest models - OpenAI's GPT-4, Anthropic's Claude 2, and the newest and open source one, Meta's Llama 2 - by posing a complex prompt analyzing subtle differences between two sentences.

Here's the prompt we gave each model:

"Tell me the main difference between the sentences 'John plays with his dog at the park.' and 'At the park, John's dog plays with him.' Explain in 180 characters."

Limiting the answer to 180 characters forced the models to be concise and accurate. Here's how each one responded:

Llama 2

Llama 2 provided good detail about sentence structure and emphasis. However, it misleadingly labeled the second sentence as SOV, when English is SVO. The technical terminology could confuse learners. It also exceeded the character limit.

GPT 4

GPT 4 pointed out the change in subject between the sentences, but didn't analyze the deeper implications of meaning and emphasis. The brevity left us wanting more explanation.

Claude 2

Claude 2 identified the main difference - the subject change - but also failed to address the impact on style and emphasis. More nuance would have improved its response, though it did respect the character limit.

Testing models on complex language tasks reveal their capabilities and limitations. While these three are highly advanced, they still struggle with nuanced linguistic analysis and clear, concise communication. As these models progress, we look forward to seeing improvements on tricky prompts that require real comprehension.

Let us know what you think about these results! What other tests would you suggest to compare AI language models? We’re curious to hear your thoughts.

Also, don’t forget to subscribe to see the next experiment’s (We’re uploading Llama’s 77 pages technical whitepaper and asking questions from the doc to these models) results.