Aider + NextJS + O1 & O1-Mini : Generate FULL-STACK Apps in JUST ONE PROMPT (Better than Claude?)

Summary

This video discusses OpenAI's new 01 model and its performance on the AER benchmarks, scoring 79.7% on code editing tasks. It compares 01 with other models like Sonet and GPT-4, noting that while 01 performs well, it's more expensive and has rate limits. The video demonstrates using AER with 01 to create a book management app and a calorie tracker app, suggesting Sonet might be a more cost-effective choice for coding tasks due to its prompt caching feature.

Takeaways

• 🚀 OpenAI has launched a new model, 01, which excels in various tasks including coding, math, chemistry, and biology.
• 📈 The 01 model has achieved top scores on the AER benchmarks, completing 79.7% of the questions and scoring 100% in the correct edit format.
• 🏆 The 01 preview model's performance on AER's code editing benchmark is state-of-the-art, suggesting it's among the best in its class.
• 💾 The whole edit format, which returns a full copy of the source code file with changes, is deemed more practical for use.
• 📊 Using the diff edit format, which returns search and replace blocks, the 01 preview model scored 75.2% on the AER benchmark.
• 💰 The 01 Mini model is priced similarly to GPT-4 and Claude 3.5 but scored below them, indicating a lower cost-to-performance ratio.
• 🚫 OpenAI's API access to the 01 model is restricted to tier five members of the OpenAI Enterprise API, imposing rate limits and high costs.
• 🛠️ AER's team is working to optimize prompts and edit formats to better utilize the 01 models.
• 💻 The video demonstrates using AER with the 01 model to create a Next.js project for a book management app, showcasing its capabilities.
• 📊 The 01 Mini model was also tested, creating a calorie tracker app, but with some minor issues, suggesting room for improvement.
• 🤔 The presenter concludes that Sonet remains a better coding model due to its cost-effectiveness and prompt caching, despite the 01 model's high performance.

Q & A

What is the new model launched by OpenAI?

OpenAI has launched their new 01 model.

What capabilities does the 01 model have?

The 01 model is capable of handling tasks ranging from coding to math, chemistry, biology, and various other domains.

How does the 01 model perform on AER's benchmarks?

The 01 model has achieved a high performance on AER's benchmarks, scoring 79.7% on the code editing benchmark and 100% using the correct edit format.

What is the significance of the whole edit format in AER's benchmarks?

The whole edit format allows the model to return a full copy of the source code file with changes, which is considered more practical and efficient for editing source code.

How does the 01 Mini model compare to other models in terms of pricing and performance?

The 01 Mini model is priced similarly to GPT-4 and Claude 3.5 but scored below those models in benchmarks. It works best with the whole edit format.

What challenges does the 01 model face with AER's diff edit format?

The 01 model had trouble conforming to AER's diff edit format, which might be due to the model's own processing formats that make it harder for users to adapt to custom formats.

What is the current limitation for using the 01 model through OpenAI's API?

API access to the 01 model is currently limited to tier five members of the OpenAI Enterprise API, and even then, there are rate limits such as 20 requests per minute.

How can one use AER with the 01 model?

To use AER with the 01 model, one needs to install or update AER, set the OpenAI API key, and start AER with the 01 model. If using OpenRouter, set the OpenRouter API key and start AER with the 01 model.

What is the reviewer's opinion on the cost-effectiveness of the 01 model compared to Sonet?

The reviewer suggests that Sonet is more cost-effective and performs better for coding tasks, despite the 01 model's capabilities.

What is the reviewer's overall impression of OpenAI's recent model launches?

The reviewer has been somewhat disappointed with recent OpenAI launches due to issues that make them less suitable for most use cases and hopes for improvements in usability and cost reduction in future releases.