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We allow early voting. This is against what most arenas do, but is on purpose. If the model is faster to do simple stuff, it should be chosen. In this sense, DS4.1-Flash is better on many tasks.

You can remove early voting from leaderboard and they are no longer the same.

by purerandomness11 hours ago|

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At the point where I choose an expensive model like Kimi 3.1, speed doesn't matter, at all.

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.

by seizethecheese7 hours ago|

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I think you’re alone to think time for task completion doesn’t matter

by rocho2 hours ago|

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But his point is that the faster models could _not_ complete the task satisfactorily.

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.

by nostrebored12 hours ago|

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But how do you verify a fair or representative distribution of complexity?

by seizethecheese7 hours ago|

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We validate people are doing real work using LLM judges.

by haizhung4 hours ago|

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I tried both of them for agentic coding and didn’t feel like K3 was adding so much benefit to justify its almost 10x price (on the modem provider I’m on).

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.