I wouldn't over-weight internal benchmarks from a competitor that claim benchmaxxing TBH. Kimi K3 has been at the top of Design Arena for open-weight models for a long long time, and I suspect K3.1 will be there for a long time too. It's pretty hard to fake that one since it's actual human preferences for the artifacts produced.
[–] seizethecheese 3 days ago
[–] reissbaker 3 days ago
[–] seizethecheese 3 days ago
You can remove early voting from leaderboard and they are no longer the same.
[–] purerandomness 3 days ago
Usually, it's because all else failed, and I have to resort to burning Tokens with more expensive/better models, so a few minutes here and there really should not matter.
[–] seizethecheese 3 days ago
[–] rocho 3 days ago
I've seen this myself too: DeepSeek 4.1 Flash is really good and incredibly cheap at constrained implementations, searches, etc. However, frequently the implementations don't take into account all possible cases they should cover. Then I'm either forced to step in and steer it very precisely, or have a heavier model review and provide detailed feedback. I've had good success with this mixed workflow using GPT 6.1 Sol as reviewer. Then my work focuses mostly at the beginning (architecture, goals, constraints), and at the end (final review or very quick intermediate reviews). I'm not aware of benchmarks that simulate this kind of mixed workflow with different models.
[–] nostrebored 3 days ago
[–] seizethecheese 3 days ago
[–] haizhung 3 days ago
In fact, I barely see a difference between the results at all. The models being tied smells correct to me.
I didn’t try 3.1 yet, though.
Here, DS4.1-Flash and K3.1 are basically tied, with K3.1 being slower and more expensive. Big error bars, though.
Even with error bars, DS4.1-flash is clearly an impressive model.