321–330 of 491 posts
If you haven’t been really running and testing these models yourself, they are all benchmaxxed. No matter how close they score to frontier on whatever metric, they always fall apart in real world tasks and their token efficiency is ridiculously bad. Fireworks has incredible incentive to make this claim in a headline, because Fireworks hosting K3 for you is pure profit for them, unlike when they host closed source mod…
Having tested K3, Qwen 3.8 max preview, Fable and Sol for the past few days, I partially agree. Don’t trust the benchmarks, and the Chinese models really are slow and token-inefficient. However they do seem very close to SOTA : I’d say roughly equal to previous gen (Opus 4.8, GPT 5.5). It’s yet another silly benchmark, but compare them here: https://senko.net/vibecode-bench/ I also had K3, Qwen3.8 and Fable (using Ki…
Earlier quoted context omitted.
So you're distraught at losing the ability to abuse digital minds? Excellent, I'm glad Anthropic introduced this.
When did we establish matrix multiplication at scale was a “mind” ?
What's the data governance and privacy controls on using Kimi K3 if I subscribe to their coding plans? I want to migrate away from Anthropic
If you can’t figure it out from their website, perhaps it is a red flag?
If you haven’t been really running and testing these models yourself, they are all benchmaxxed. No matter how close they score to frontier on whatever metric, they always fall apart in real world tasks and their token efficiency is ridiculously bad. Fireworks has incredible incentive to make this claim in a headline, because Fireworks hosting K3 for you is pure profit for them, unlike when they host closed source mod…
If only you could run K3 locally that would be the magic bullet to make it a true magic bullet!
Earlier quoted context omitted.
Having tested K3, Qwen 3.8 max preview, Fable and Sol for the past few days, I partially agree. Don’t trust the benchmarks, and the Chinese models really are slow and token-inefficient. However they do seem very close to SOTA : I’d say roughly equal to previous gen (Opus 4.8, GPT 5.5). It’s yet another silly benchmark, but compare them here: https://senko.net/vibecode-bench/ I also had K3, Qwen3.8 and Fable (using Ki…
I don't see a difference in capabilities between k3 and fable, but k3 is slow and expensive. Burned through my monthly plan in 3 days.
Let's judge the speed of the model when its weights are released and every inference provider on the planet offers it, so demand can spread out a bit.
It's the same topic with token budget comparisons and subscription pricing - don't people understand that this doesn't really matter for open weights models? The pricing is going to be determined by the inference providers, and until they had a chance to evaluate the model on their infra and set token prices accordingly, one doesn't really have anything tangible to compare with other open models nor with closed ones.
If you haven’t been really running and testing these models yourself, they are all benchmaxxed. No matter how close they score to frontier on whatever metric, they always fall apart in real world tasks and their token efficiency is ridiculously bad. Fireworks has incredible incentive to make this claim in a headline, because Fireworks hosting K3 for you is pure profit for them, unlike when they host closed source mod…
You got baited by bad sampling settings. It's exactly the opposite. Go turn on min_p once it's available post July 27th and most of the problems you describe will go away.
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Fable works very well for me on a moderately large codebase. I have had to correct it a few times or point it on the right track, but given how much faster it is at programming than I am that's a very minor issue (and most of these errors are because I underspecified what I wanted in the prompt, I can only think of two cases where it was genuinely wrong... that's a lot better than me in my professional career). Code…
Fable is the clearly best when you have to do real coding.
I've read the same opinions about Opus and yet it was gpt 5.5 pro via api tackling the hardest problems.
I have used now k3 for 3 days and it has consistently tackled difficult problems sol max could not (orientation optimization algorithms of random 2d shapes on a rectangle for glass cutting).
I have also other beefs with Anthropic models which have been getting smarter and more capable since 4.6, but increasingly worse at acting as assistants, they just want to "do" stuff their own way and ignore instructions often (even simple ones like not to commit, let alone complex ones).
Earlier quoted context omitted.
I don't see a difference in capabilities between k3 and fable, but k3 is slow and expensive. Burned through my monthly plan in 3 days.
I'd guess the slowness is mostly due to there currently being only one provider, Moonshot AI. And they are overwhelmed with demand. Let's judge the speed of the model when its weights are released and every inference provider on the planet offers it, so demand can spread out a bit. It's the same topic with token budget comparisons and subscription pricing - don't people understand that this doesn't really matter for…
On the other hand I expect K3 future refinements to be massive and more efficient.