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by scrlk1 hours ago |
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upvoteby parsimo20101 hours ago|
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The timing looks like they are trying to take the wind out of Qwen's sails by releasing this on the same day that Qwen released the weights of Qwen3.8-max. Or maybe it's coincidence...

For comparison I looked at Qwen's claimed benchmarks for Qwen3.8-max (https://qwen.ai/blog?id=qwen3.8). Assuming each published set of benchmarks is believable, it looks like v4 Pro 0813 is better on average but overall performance is comparable. Pro 0813 is much cheaper. If you don't need vision capabilities then you don't have much reason to use Qwen3.8-max.

- 43.6 on HLE (Presumably without tools). Pro 0813 is a little worse.

- 86.6 on Terminal Bench 2.1. Pro 0813 is better.

- 55.9 on NL2Repo. Pro 0813 is better.

- 27 on Agent's Last Exam. Pro 0813 is a little worse.

- 72.5 on Toolathon-Verified. Pro 0813 is better.

- 56.6 on DeepSWE 1.1. If the DeepSWE listed for Pro 0813 is the same version, then Pro is better.

- 27.3 on AutomationBench. If the AutomationBench (Public) listed for Pro 0813 is the same, then Pro is better.

I guess we do need to wait to see if the upcoming DS pricing increase is enough to change the value proposition. As it is now, they could double or triple prices and it still would be a better value to use DS. I bet they know that.

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upvoteby trollbridge1 hours ago|
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By that standard, the release of Grok 4.6 was also timed on the same day.

Given how I think DeepSeek operates... I think they just release it when they feel it's ready, and don't even seem that concerned with what other people are doing.

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upvoteby somenameforme57 minutes ago|
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Their leaks would confirm this sort of attitude. They're not trying to become the top player or anything like that - just working to play their part in pushing LLM tech forward and going from there. It was quite refreshing from the 'here's how we're going to dominate the world' nonsense. It's undoubtedly the same attitude that just lets them shrug and cancel the fund raising round after the leaks came from said funding round.
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upvoteby trollbridge49 minutes ago|
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The founder of DS's stated goal is to get to AGI. He thinks this is the path to get there.

Kind of interesting, when compared to the hubris from American frontier labs.

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upvoteby johnvanommen23 minutes ago|
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> Kind of interesting, when compared to the hubris from American frontier labs.

One Man’s “hubris” is another man’s “marketing campaign.”

Drama sells.

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upvoteby scrlk50 minutes ago|
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Benefits of having a well performing hedge fund funding DeepSeek.

IIRC, Demis attempted to start a fund inside DeepMind but it was killed off. In an alternative world where he manages to pull that off, perhaps DeepMind would still be independent with Demis at the helm.

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upvoteby surgical_fire52 minutes ago|
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Their stance on LLM development is why they earned my respect in a time when OpenAI and Anthropic only earn my mistrust.

That, and the fact that DS is an insanely capable model.

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upvoteby parsimo201053 minutes ago|
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Actually, yes. I just didn't know about Grok's release because they aren't on the front page of HN.
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upvoteby eli1 hours ago|
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Official pricing only kinda matters for an open weight model, no?
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upvoteby parsimo201054 minutes ago|
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It still matters as a point of comparison until other providers come online. If the consensus price from other providers is much different that can be compared then. But for now we have $0.435 / $0.87 for v4 Pro 0813 (with increase announced but we don't know the new pricing), and $2 / $6 for Qwen3.8-max. So until we get other data points that is what we have to look at.
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upvoteby eli46 minutes ago|
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I wondered if the promised change in pricing is actually going to be deepseek bringing up their cached costs. They're extremely inexpensive.
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upvoteby maherbeg59 minutes ago|
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I mean at the rate of model releases happening, I think a lot of these will collide more often than expected!
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upvoteby goldenarm1 hours ago|
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Geometric mean of all these benchmarks :

* GPT-5.6 Sol: 65.5

* Fable 5 (w/ fallback): 64.5

* Opus 5: 64.0

* DS-V4-Pro 0813: 62.5

* Kimi-K3: 62.3

* DS-V4-Flash 0731: 55.8

* GLM-5.2: 47.3

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upvoteby svachalek24 minutes ago|
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Maybe it's me but I don't see how DS Flash is better than GLM at all, much less by a huge gap. I'd probably protest less against Fable and Opus being put at the same level than many would, but there's no denying the two models are a very different experience from each other. I guess where I'm going is no one should pick a model by the benchmarks.
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upvoteby platinumrad5 minutes ago|
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I think instruction following carries outsized weight in these evaluations.
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upvoteby bel81 hours ago|
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So it's a Fable class LLM?

                             DSV4Pro vs Fable5
    HLE w tools              60.0 vs 63.0
    Terminal Bench 2.1       87.9 vs 88.0
    Cybergym                 83.3 vs 83.1
    DeepSWE                  62.7 vs 70.0
    Toolathlon-Verified      74.1 vs 77.9
    AutomationBench (Public) 31.8 vs 29.1
    DSBench-FullStack        71.1 vs 77.2
    DSBench-Hard             67.2 vs 68.3
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upvoteby eli1 hours ago|
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Fable's guardrails would never let it do something like Cybergym so at least for that one it's measuring Opus 5
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upvoteby wren699159 minutes ago|
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We have a first-party figure from the system card [1]:

> Mythos 5 reproduced 83.8% of targeted vulnerabilities on a single try, and produced at least one crash in 99.4% of tasks. This is comparable to Claude Mythos Preview, which reproduced 83.1% of targeted vulnerabilities and produced a crash in 97.1% of tasks. By contrast, Claude Opus 4.8 achieved a score of 78.1% (95.7% any crash).

So their quoted figure exactly matches the figure for Mythos Preview, although they don't state the provenance. It could also quite possibly be an independent measurement of Opus 5.

[1]: https://www-cdn.anthropic.com/57a52ea7d8f0e54e8a542e90826608...

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upvoteby aftbit1 hours ago|
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Fabble lol
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upvoteby qiran8732 minutes ago|
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[dead]
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upvoteby NietTim22 minutes ago|
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In classic reddit fashion the post you linked to is now deleted
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upvoteby SV_BubbleTime15 minutes ago|
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To be fair… I don’t know who still needs to figure out that AI benchmarks are almost all entirely fucking trash, but the great number would surely surprise me.
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