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Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

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Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#441

Post by tracker1 »

Kind of cool to see.. that said, there's more to a tooling experience than benchmarks and specific models. Cursor, Claude Code, Codex, etc. add to the mix. Things like Open-Router and backend options make it easy enough to test.

The tools, libraries and languages you are using can also dramatically affect results. Even on state of the art models, I find, for example, the output of SQL for complex interactions, or C# for that matter to be sub-par, where I find Rust results to be pretty great, with JS/TS falling in between.

At the best, it can feel amazing and productive, at worst, time consuming and annoying that you could have done it faster yourself. YMMV in real world use.

Note: I'm a proponent of human in the loop gatekeeper/reviewer usage of AI, and I'm not able to even consider Chinese models for my own use, and not able to use anything at my day job.

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#442

Post by hereme888 »

thecopy wrote: post #388

When DeepSeek was released, it had an immidiate and significant impact on the US stock-market. Now when its becoming common knowledge that China is almost at parity with US SOTA models with good momentum, why is there no sentiment change on the market?

Because the markets learned Chinese = fake results

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#444

Post by notatoad »

thecopy wrote: post #388

When DeepSeek was released, it had an immidiate and significant impact on the US stock-market. Now when its becoming common knowledge that China is almost at parity with US SOTA models with good momentum, why is there no sentiment change on the market?

there was a significant impact on the market because the market assumed that a strong cheaper model would have a significant impact on the US AI companies' business. That didn't happen.

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#445

Post by kian »

raesene9 wrote: post #393
terekhindc wrote: post #387

the per-token comparison keeps missing that k3 spends way more tokens per task. if it burns 3x tokens to reach the same result as fable, cheap per-token stops mattering

They address that in the article :) to quote :- "So where's this huge price gap coming from? token pricing, prompt caching, and effort-per-task. On SWE for example, K3 works much harder than Fable: roughly 55 turns and 1.3M tokens a task versus 21 turns and 130K. On the long terminal tasks it's the other way around: Fable is the one that spirals, running up 64 turns and 1.5M tokens (sometimes straight into a timeout)…

So this makes sense for a standard SaaS app - but given that models in general perform much better with low context window usage, it probably also means that Fable is still significantly better at 'frontier-level tasks' -- hard research problems, complex geometric rendering algorithm optimization, etc., no?

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#446

Post by maxignol »

lumost wrote: post #409
senko wrote: post #276

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…

Honestly my anecdotal experience is that fable is benchmaxxed. I have not observed useful gains for Claude since 4.6, with each model iteration making progressively poorer decisions in pursuit of its goal. The 5.5/5.6 series has performed quite well however. My guess is that my use cases stop aligning to swebench pro around 50% accuracy, and more closely align with DeepSWE.

> my use cases stop aligning to swebench pro around 50% accuracy, and more closely align with DeepSWE.

What do you mean by that ? If the model is higher than 50% on swebench pro then it tends to drift from what you like it to do, like DeepSWE benchmarks ?

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#447

Post by maxignol »

epolanski wrote: post #329
llelouch wrote: post #283

Earlier quoted context omitted.

Fable is the clearly best when you have to do real coding.

Clearly, for you. 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,…

What is your harness with every model ?

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#448

Post by ainch »

nxtfari wrote: post #253

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…

It's telling that in their release post, Moonshot themselves said that K3 lags Fable and GPT-5.6 in "user experience". I took that to mean the stuff you can't push directly via RL, what some people call "big model smell".

"Despite being a highly competitive model overall, K3 nonetheless exhibits a noticeable gap in user experience compared with Claude Fable 5 and GPT 5.6 Sol."

https://www.kimi.com/blog/kimi-k3

Re: Kimi K3 Is Competitive with Fable; Kimi K3 and Fable Is SoTA

#450

Post by uejfiweun »

krige wrote: post #300
uejfiweun wrote: post #285

Earlier quoted context omitted.

All you've said needs the qualifier - "for now!" Look at the trend line. It's clear that if they're not yet at the level of being "good enough" for coding, they will be soon. Sensationalist headlines aside, we all need to be preparing for a world where open models can do pretty much any software tasks you need them to.

https://xkcd.com/605/

This is such a smooth-brain reply, dude. The capability literally exists, today. You're telling me that it's just SO fantastical that people will be able to catch up? Give me a break. Anthropic and OpenAI are not staffed by demigods.
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