Morocco's whole history of participation is only since 2017? So I guess it's the results are pretty normal especially with limited ressources. My advice for you is that you focus on math given that the fact that you are in a an early stage, use Mathtraining.be (used by french speaking countries) or AOPS, meanwhile practice for time to time your coding skills but once you see urself you have a decent level you try to jump back practicing programming contest more seriously and you will improve much faster.

I agree that these are bold claims that require proof, but I don't think OpenAI is interested in or investing time in making their model more optimal for programming contests. As for the 400 rating, I'm sure it's based on the raw output from OpenAI's API. If you understand my comment, you'll see that I'm not claiming it always provides the correct solution on the first try. However, in many cases, the way the user feeds the model samples and prompts helps the model debug or fix the code. In any case, I will post the proof as soon as I can.

I don't recall claiming that it can solve the contest in 15 minutes. Are you now challenging whether it can solve the problem, or are you questioning the speed at which it can solve the problem? Either way, at least the last time, it managed to ace a Div4 contest in around an hour.

This is one of the reasons I didn't want to post such comment. And I'm not here to argue but anyways I will record a screencast of gpt4 solving div3 or div4 contest and I'll share it publicly and we'll see if it's a troll.

I've been contemplating sharing my observations on a this topic, and I believe it's the time to share things anyway.

I have conducted several experiments using LLms to assess their performance in various programming contests. Among the models I tested, GPT-4 has consistently stood out, hence I predominantly utilized it. To enhance its capabilities, I integrated an agent on top of GPT-4 that automates the processes of code writing, testing, and evaluation. Additionally, I employed prompt engineering to simulate a chain of thought.

The results have been quite astounding. I allowed the model to participate in three contests autonomously, and it achieved impressive scores of +1900 and +1600 in div3 and div4 contests "fully solved a Div4", respectively. I've also observed that the manner in which the problem statement is presented to the model significantly impacts its performance. On occasion, minor interventions are required to guide the model to the correct solution.

For those interested in replicating my findings, I recommend using ChatGPT Plus combined with a code interpreter. The outcomes should be commendable. As a side note, my current configuration of the model has a rating of +2000 on LeetCode and even achieved a +2400 performance rating in one of the rounds.

I'm sharing this to highlight the potential of such models. While many believe these models don't make a significant difference, I speculate that an advanced model beyond GPT-4 could potentially solve even Div1 problems.