421–430 of 491 posts
Earlier quoted context omitted.
Is that any worse than being subsidized by VC? They're playing the same game as the western labs, just with slightly different players.
Chinese government vs American VCs doesn't equate to "slight different players."
They might not always live up to that, but at least the aspiration is there.
No such pretense from American VCs.
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…
There are some benchmarks I personally trust. But the most reliable indicator other than public benchmarks is the quality of products people are working on, and the model they use for the work. Not a benchmark scoreboard or a one~few shot demo, but the product they have been building for weeks. The reality is, even the diehard advocates who build and sell tooling for open weights, still use proprietary frontier model…
(And, yes, I know we should blame C. C turns every bug into a cybersecurity nightmare.)
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?
Earlier quoted context omitted.
I'm not. But I'll concede you are possibly more literate - I won't dox myself on this account. Congratulations. If you honestly argue that LLM computation and human cognition are equivalent there is no further argument to be had - it's immediately a philosophical or worse a religious argument that cannot be won. However, that we're even arguing on that level baffles me. How did this happen! They're glorified calculat…
> uses a specific, objectively nonsensical critique of LLMs (the idea that an algorithm using matrix operations as a primitive cannot emulate "true" intelligence) > receives pushback on the specific, objectively nonsensical critique > "oh so you're saying that LLM computation and human cognition are equivalent? they're glorified calculators that disprove the Jacobian conjecture!!!"
I did not say that. Not even close.
In the words of Claude: I’ll end the conversation here.
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.
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…
Kimi was half the cost and produced a near identical output.
On a fairly simple coding task Kimi was 2x the cost and 7x as slow (and gpt-5.6-sol was even cheaper).
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…
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?