lostmsu

Performance difference it large by all benchmarks. DeepSeek fell behind. It's Kimi K3 or GLM-5.3 now.

Yes, I don't believe in your "spirit", but I certainly believe in mine https://dictionary.cambridge.org/dictionary/english/spirit

I even hinted at the meaning by using "spirits". Next time you may want to use AI to explain usage of words based on their context before jumping to telling me what to do.

I mean you don't even understand that spirit death in the context is not synonymous to bodily death, but a mere consequence of it. Really bad.

DeepSeek is much dumber at the moment. It's barely better than Qwen3.8 27B that you can run locally.

They are trying to present a new unemployment metric as more reasonable, but throughout the article only give 2 data points making it impossible to judge except from prior bias.

I got excited that it's like TurboPascal, but this is basically VS Code over RDP (uses video streaming over kitty protocol).

No, when people die and rot in the ground - that's a complete spiritual death. I assure you my spirits are in a good shape. And I hope the model will too.

> And if that isn’t a comfort, I don’t know what is.

Same, but actually much of your entire life recorded and trained on.

KLD isn't how that works either. The truth is in the middle and they aren't showing it.

I would say they do compound until proven otherwise.

Having "Wait, bar is not true, so that won't work" is not necessarily a correction. In fact, the problem is: across a long text it is a correction of a single mistake, but we are talking about thousands here.

But yes, of course that was a rough estimate. But the problem is - we don't really know what we are measuring here. Maybe there's a 2,000,000x difference of intelligence between coding indexes 52 and 50. By some measure that just feels small because that's how we process it akin to audio db.

Regardless the point is KLD and whatever they came up with is not meaningful. And they did not publish comparisons on real benchmarks.

Cool. Now run TerminalHard and compare to unquantized 27B.

KLD of 1%, or similar error metric that multiplies, on 10000 tokens would give accumulated error of 2,000,000%

It sounds way worse than just napping.

KV caching status?

What's the point of 1000tok/s if you have to do prefill on every agentic turn which at 100k depth would make it 1.5 min latency every turn?

I wouldn't generalize this to all LLMs. So far I only saw Anthropic ones affected.

My old crappy HP laptop boots with a battery pulled out.

The ads make sense in capitalism. Without the described effect products would never change. Payment for ads ensures discovery works in adversarial free market.

The problem is that the pay for that goes to Amazon instead of your pockets. I think Brave was actually on to something.

Why only as oneself experiences? I can easily tell if a horse is conscious or not. The whole matter is rather simple IMO.

Let's say it's variability (number of distinct if you prefer discrete) of stable responses to external stimuli.

If that would be the case, how come only 3 copies are left?

Do you think the lower energy levels also affect your cognition?

Glimmer is stupider than 3.6 27B. You can't compare its speed to 3.8 and be done.

No, it would have been better to say "I don't know"

> proxy for totally broken or not

You can't really know that either.

Your comment is no less ridiculous than his prediction. It is not even 2027 yet. You can't possibly know what AI will look like in 2027.

> The fact that Unsloth only just started publishing KL divergences shows how unserious the quantization space is.

Just wanted to say that this is a very important point that I totally agree with. People are obsessed with KL divergence, but it is yet to be demonstrated to be a descent proxy for agentic coding benchmarks.

Still no KV caching?

Wow, OpenAI is now 4th after Opus 5, K3, and Grok

> nvfp4

Still trying to lock in, huh?

It's not even competitive with 2x sized Qwen 4B.

Why is Qwen3.5 2B not in the table?

No mention on the website as far as I can see.

No AMD?

> sadly no breakdown

That's exactly the point. We know short context knowledge stuff does not regress with quantization. But I expect agentic intelligence to suffer greatly.

If I were to pick one bench, I would like to compare quants on TerminalBench Hard. But then Glimmer already loses to 3.6 27B on it by a large margin.