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DeepSeek v4

api-docs.deepseek.com

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Re: DeepSeek v4

#951

Post by wohoef »

hodgehog11 wrote: post #461
lifty wrote: post #341

Earlier quoted context omitted.

Wondering how gpt 5.5 is doing in your test. Happy to hear that DeepSeek has good performance in your test, because my experience seems to correlate with yours, for the coding problems I am working on. Claude doesn't seem to be so good if you stray away from writing http handlers (the modern web app stack in its various incarnations).

Very cool to hear there is agreement with (probably quite challenging?) coding problems as well. Just ran a couple of them through GPT 5.5, but this is a single attempt, so take any of this with a grain of salt. I'm on the Plus tier with memory off so each chat should have no memory of any other attempt (same goes for other models too). It seems to be getting more of the impressive insights that Gemini got and doing…

Do you an idea of how well these models perform on set theory problems or more niche fields in mathematics? So the model would have to both understand a paper that’s not in its training data, and use this to write proofs.

Re: DeepSeek v4

#953

Post by tw1984 »

Squarex wrote: post #838
gertlabs wrote: post #788

Objective, detailed benchmark results at https://gertlabs.com Early takeaways: from this release, DeepSeek V4 Flash is the model to pay attention to here. It's cheap, effective, and REALLY fast. The Pro model is slow, not much better in coding reasoning so far when it works, and honestly too unreliable and rate limited to be of much use, currently. Hopefully that improves as new providers host the model. Flash is wor…

I would say all benchmarks are inherently subjective. How is yours better? It seems to produce a little bit strange results. Opus 4.6 being worse than 4.5 for example. Or chinese models being rated too high. Kimi, Deepseek or GLM are all great in open source world, but I don't believe they are ahead of SOTA models from Anthropic, OpenAI or Google.

I agree that benchmarks are inherently subjective.

but the fact that you cite your brief as your main argument is funny - you don't even have any inherently subjective numbers to justify what you believe, you only have "I don't believe".

Re: DeepSeek v4

#954

Post by dataviz1000 »

hodgehog11 wrote: post #304

There are quite a few comments here about benchmark and coding performance. I would like to offer some opinions regarding its capacity for mathematics problems in an active research setting. I have a collection of novel probability and statistics problems at the masters and PhD level with varying degrees of feasibility. My test suite involves running these problems through first (often with about 2-6 papers for conte…

> there is no quantitative measure of performance here

Have them do multiplication or other complicated arithmetic. You say that isn't difficult. Then why do they burn 200k tokens in 20 minutes without converging? I did a deep exploration to help myself understand here [0].

[0] https://adamsohn.com/reliably-incorrect/

Re: DeepSeek v4

#955

Post by edg5000 »

Kuyawa wrote: post #710

I am using DeepSeek extensively to develop apps, three in the last month, with my own CLI coding agent [1] developed by DeepSeek itself line by line. I haven't spent $1 yet in well over 10 million tokens. If I considered myself a 10X programmer, now I am 100X. Love DeepSeek. [1] https://github.com/kuyawa/mecha-ai

Have you compared it against other coding agents? What is your general workflow with DeepSeek; do you write a spec and then have it implement and test? Very interesting to hear. Becuase your harness is adapted to DeepSeek, you probably prompt and it very differently; since its adapted to the model this may explain why it works well for you. Wiring up an existing harness that is not tested on DeepSeek may not yield optimal results.

Re: DeepSeek v4

#956

Post by zrn900 »

TrackerFF wrote: post #333
jari_mustonen wrote: post #239

Open Source as it gets in this space, top notch developer documentation, and prices insanely low, while delivering frontier model capabilities. So basically, this is from hackers to hackers. Loving it! Also, note that there's zero CUDA dependency. It runs entirely on Huawei chips. In other words, Chinese ecosystem has delivered a complete AI stack. Like it or not, that's a big news. But what's there not to like when…

Let's see how long it takes before the big US AI companies start lobbying to outright ban use of Chinese AI, even the open source / local models. For "national security" reasons, of course.

They already did - State Dept. launched global campaign against Deepseek.

Re: DeepSeek v4

#957

Post by madduci »

throwa356262 wrote: post #217

Seriously, why can't huge companies like OpenAI and Google produce documentation that is half this good?? https://api-docs.deepseek.com/guides/thinking_mode No BS, just a concise description of exactly what I need to write my own agent.

For me, DeepSeek has been the best so far, in terms of coding skills, performance and documentation all together. Too bad this is flagged as 'concerning' when it comes to privacy, while on the other hand Gemini, ChatGPT and Claude are way beyond that, especially their mobile apps requiring a lot of permissions.

Re: DeepSeek v4

#959

Post by Rover222 »

mike_hearn wrote: post #808
Rover222 wrote: post #772

Quite jarring to see how many people think the Chinese authoritarian regime, and the tech that it allows to be created in that country, are going to be "safer" or whatever than US tech. It's trendy to say the US govt is now authorization, but that's just pure naïve groupthink.

It's just the anti-Americanism that has typified the Euroleft for decades. You can find people complaining about it back in the 1800s. As can be seen by how much American product Europe consumes it's not actually an influential mode of thought, just a form of ingroup signalling, so it can largely be ignored.

But it's now mainstream thought on the left in America.

Re: DeepSeek v4

#960

Post by chid »

segmondy wrote: post #841
lowbloodsugar wrote: post #764

Earlier quoted context omitted.

You run a 671B model at home?

Yes, and plenty of others do too. Quantizied. Join us at r/localllama My largest models 318G /llmzoo/models/Qwen3.5-397B 377G DeepSeekv3.2-nolight 380G /llmzoo/models/DeepSeek-V3.2-UD 400G /llmzoo/models/Qwen3.5-397B-Q8 443G DeepSeek-Math-v2 443G DeepSeek-V3-0324-Q5 522G /llmzoo/models/GLM5.1 545G /llmzoo/models/kimi2.6 546G /llmzoo/models/KimiK2.5

even quantised, those are HUGE
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