m-dot-reviews

4 ms·

1. 1.▲
   by m-dot-reviews 3mo ago

   I've been plugging this perhaps too many times now, but I am trying to bootstrap a user-sourced corpus of exactly "what model is good at task X". So, not benchmarks, but high-level tasks. There's a bit of a ordering prob
2. 2.▲
   by m-dot-reviews 4mo ago

   Oops, thanks for telling me that. I think the issue should be fixed now.
3. 3.▲
   by m-dot-reviews 4mo ago

   So, this may not be precisely what you're looking for but it may come close. I've put together a simple site for sharing ratings/opinions on models on a task-specific granularity. https://model.reviews/ The i
4. 4.▲
   by m-dot-reviews 4mo ago

   For anyone who's interested, I've put together a simple site for sharing ratings/opinions on models at a task-specific granularity. https://model.reviews/ The idea is that benchmark score comparisons are usef
5. 5.▲
   by m-dot-reviews 4mo ago

   I'm starting a repository of LLM reviews [1] with the goal of creating a catalog that is more task-oriented and less marketing-y than corporate blogs or benchmark leaderboards. You seem to have a lot of experience across a bunch of dif
6. 6.▲
   by m-dot-reviews 4mo ago

   Anecdotally, yes there is definitely a difference. Even e.g. Haiku (cheapest Anthropic model) vs gpt-oss-120b had a big difference in quality and syntax issues when I was testing them for DSL generation. Granted, that's a little differ
7. 7.▲
   by m-dot-reviews 4mo ago

   I looked for a forum like this a few months ago during my own model research, and didn't find one. So, here's the "catalog of clankers," a task-structured review site for LLMs. The idea is that if you're looking for