7 Coding LLMs, 1 Prompt—Here’s What I Found

The speaker tested seven different AI models using the same prompt and presented the results. The models include Number One, Number Two, Number Three, and up to Number Seven. Models like Opus 4 and Sonnet 4 were compared for AI coding assistant tasks, with Opus 4 performing relatively better in terminal coding tasks.

Opus 4 was highlighted as the best AI coding assistant model based on tests. It outperformed other big models like Sonnet 4, excelling in tasks involving cursor movement, file deletion, and long agentic processes. However, Opus 4 was noted to be lagging behind previous versions in performance.

The pricing comparison of different models was discussed, with Opus 4 priced at $75 per million output tokens. In contrast, Gemini was deemed the most cost-efficient at $15 per million output tokens, making it a viable alternative for users concerned with pricing.

The speaker discussed testing all models for web search capabilities, highlighting a specific sequential tool that synthesizes information from web searches. Models like Clot 4, Opus 21, and LLama 4 were tested for their efficiency in gathering and synthesizing information from the web.

The speaker evaluated and compared different models based on their inclusion of Clot 4, O3, and Cloud 4. Models like Cloud 4 and O3 were assessed for accuracy in capturing release dates and model parameters, with each model exhibiting variations in information synthesis and benchmark accuracy.

The speaker provided insights on model selection, expressing a bias towards Gemini 2.5 Pro for its cost-efficiency. While Gemini 2.5 Pro was recommended for its affordability, users were advised to consider performance factors when choosing a model for their tasks.