The AI Model You Use Doesn't Matter (Here's Proof)

The speaker introduces GM Tech, a valuable resource for comparing various large language models and image models from platforms like OpenAI, Google, MOL, Amazon, Anthropics, and AI 21.

GM Tech allows users to compare various AI models like GPT-3, GPT-4, LLAMA 2, CLA 3 Sonet, and Gemini Pro. The tool provides insights into response time, cost, and formatting differences among these models.

The speaker tests the creativity of different models by requesting unconventional business ideas. Models like GPT-4, LLAMA 2, CLA 3 Sonet, and Gemini Pro are compared based on their speed, creativity, and cost.

Various language models are tested for their humor skills by generating jokes. Results show similarities in joke responses among models like GP4, LLAMA 2, CLA 3 Sonet, Gemini Pro, and Mistal Large.

The models are asked to predict a number between 1 and 100, with a high occurrence of the number 42. The reason behind this frequent prediction is explained, showing common outputs across different models.

The speaker explores image models like Stable Diffusion 3, comparing their performance in generating images based on prompts. Models like SDXL, DALL-E 3, Stable Diffusion 3 Turbo, and Imagin are compared for prompt adherence and cost.

The speaker reflects on the convergence of large language models and the difficulty in differentiating them for common use cases. Factors like cost, ease of use, and development capabilities are highlighted as crucial in choosing a model.