Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line

Re:Kimi K3.1 scores 55 on Artificial Analysis, placed on the... by stymaar on Friday October 23, 2026 @04:30PM (#50214901)

It really depends on the type of task you're doing and how you're using it, because for the past two month the only reason I've had to use my company's paid Opus plan instead of my local Qwen-3.8-Next was speed. I use Qwen as a back-up plan when my token limit is reached and in my day to day work they have been indiscernible in terms of output.

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Re:Kimi K3.1 scores 55 on Artificial Analysis, placed on the... by lnenad on Friday October 23, 2026 @04:35PM (#50214965)

I agree, but my point wasn't about being able to use a weaker model, it's about benchmarks not being in any way representative of the actual quality/level of the model. Of course for a lot of scenarios Opus is overkill and Qwen/DS are more than enough.

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Re:Kimi K3.1 scores 55 on Artificial Analysis, placed on the... by CharlieDigital on Friday October 23, 2026 @04:55PM (#50215197)

I think also heavily depends on what you're doing.

If you're in a stable codebase with lots of best practices, patterns, controls (linters, analyzers, etc.), examples already established, then any model will do ~the same plus/minus since there's not much novelty.

If you're building ground up, entirely novel, no reference, I think results will vary with lower capability models.

For me, I do a mix, leaving implementation to Haiku/Luna/DeepSeek and research/feedback/critique to Opus/Sol/Astra/Fable

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