Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

DeepSeek V4 Flash 0731

arcprize.org

Post reply on HN
Print view View original

231–240 of 478 posts

Re: DeepSeek V4 Flash 0731

#231

Post by [deleted] »

namr2000 wrote: post #213
ak_t wrote: post #164

Note this is the 07/31 release of DSv4 flash and not the "preview" that they put out a couple months or so ago. I've been running this model locally for a week, and the preview version before that. This updated one feels like a whole tier up. It's very capable for debugging and analyzing documents/data I upload. The killer feature, IMO, is the speed. On 2x RTX Pro 6000 Blackwell, its ~8k tok/s prefill and ~250 tok/s…

What runtime are you using with the 2x RTX Pro 6000 Blackwell machine? I have the same setup and tried DSv4 Flash on vLLM and ran into a ton of kernel bugs that don't seem to have been fixed yet.

[deleted]

Re: DeepSeek V4 Flash 0731

#232

Post by ghosty141 »

zmmmmm wrote: post #218

it's great but we need a multi-modal model of this quality and price to truly declare victory. But it makes me quite curious, how a text-only model can do so well on ARC-AGI-2 being a set of visual puzzles? It would have to solve it entirely using text-only spatial reasoning about the grid (or maybe writing code?). I am curious if this is normal or do other models use their vision capabilities to solve the puzzles?

xiaomi mimo is very cheap and not bad.

Re: DeepSeek V4 Flash 0731

#233

Post by indigodaddy »

rpdillon wrote: post #113
amelius wrote: post #88

Earlier quoted context omitted.

> it's good enough to use it for (almost) everything which in your case is?

I've posted a few times about my project that's a collection of 30k-250k webapps that are served from a WebDAV server. The apps know how to write updated copies of themselves back to the server. My family uses it. I have gallery apps (yearbooks for each year are a lot of fun!) of us on trips and just living, an outlining app that's a mesh of Workflowy and Org Mode (it's called Fluxtral), a markdown-backed app (it use…

Sounds fascinating! A blog write-up about your platform would be a fun read, if you're up to it

Re: DeepSeek V4 Flash 0731

#234

Post by ignoramous »

kzrdude wrote: post #212
ignoramous wrote: post #155

Earlier quoted context omitted.

> My initial thought was to sign up for ChatGPT, but I had $20 in OpenRouter so I've been trying out DeepSeek V4 Pro with Pi for the last few days and I gotta say, it's good enough for my use case If you prefer subscriptions, OpenCode Go ($10/mo), Cline Pass ($10/mo), Atlas Code ($20/mo), and CommandCode ($1/mo) serve some of the best open weights with generous limits. OpenCode Go currently offers $120 for $10 on Dee…

Just trying to understand, https://opencode.ai/docs/go/#privacy currently says DeepSeek V4 Flash has 0 days data retention. > DeepSeek V4 Flash: ZDR agreement is renewed monthly. The current agreement is valid through August 31, 2026. Is there other info I should be aware of w.r.t data retention with opencode go? It's hosted in China, so other middlemen may be active (I doubt it, but possible)?

That's a recent addition I wasn't aware of. Thanks. Previously, OpenCode docs claimed they had no agreement with DeepSeek on data retention for training. Even more previously, OpenCode said they used providers based in US/EU/Singapore (which they no longer do so).

Re: DeepSeek V4 Flash 0731

#235

Post by 0xbadcafebee »

anon373839 wrote: post #223
kzrdude wrote: post #212

Earlier quoted context omitted.

Just trying to understand, https://opencode.ai/docs/go/#privacy currently says DeepSeek V4 Flash has 0 days data retention. > DeepSeek V4 Flash: ZDR agreement is renewed monthly. The current agreement is valid through August 31, 2026. Is there other info I should be aware of w.r.t data retention with opencode go? It's hosted in China, so other middlemen may be active (I doubt it, but possible)?

Yes. There is a big question mark about whether Anomaly itself (as the OpenCode Go middleman) retains data. The docs were completely silent on this the last time I checked.

According to this code (https://github.com/anomalyco/opencode/blob/dev/packages/cons...) only Grok and Luna have 30-day retention, the rest have 0-day retention. Of their legal documents, none mention data retention for anything other than personal data. The exception is if you '/share' which explicitly gives them your session to share over the web with others.

Re: DeepSeek V4 Flash 0731

#236

Post by odo1242 »

anal_reactor wrote: post #222
abixb wrote: post #162

Earlier quoted context omitted.

If what you're saying is true and accurate, then US-based AI labs are in big trouble. The only saving grace might be some sort of a 'national security' proclamation banning the use of state-of-the-art Chinese (and non-US) models across US federal and state governments and large enterprises (especially ones with federal government contracts), but even still, US AI labs will probably lose out massively on international…

It's been true for almost every business. "Cheap and good enough" usually trumps "excellent but expensive". Ikea, McDonald's, Ryanair, AliExpress, Aldi - these brands prove that catering to poor people is more profitable than catering to rich people simply because there are so many poor people that their collective spending power outweights the one of rich people.

Well, not universally. It’s a tradeoff. If what you said was universally true Apple wouldn’t exist; Spirit Airlines wouldn’t be bankrupt, etc.

Re: DeepSeek V4 Flash 0731

#237

Post by LaurensBER »

m101 wrote: post #227
LaurensBER wrote: post #9

I've been using it extensively since the release and the best summary I can give is that it's good enough to use it for (almost) everything and cheap enough that the cost are irrelevant. I'm running it in Oh My Pi with a second instance running as "advisor" and even with 5-6 active sessions (effectively 12 streams) I'm struggling to spend more than 5 bucks per day. OpenCode Go even has double limits temporarily so fo…

Could you go into how you run two instances that speak to each other in an implementer / advisor role in parallel? I’ve been looking for this sort of orchestrator / worker solution where there’s constant feedback and nudging between the two.

Sure! It's https://omp.sh/ with the advisor mode enabled.

You can probably implement something similar as a plugin for your preferred harness. From a technical perspective I think it just sends the output w/h the thinking and tool trace to another model and asks it to double check everything (exact prompt must be somewhere in the OMP repo).

Re: DeepSeek V4 Flash 0731

#238

Post by gizmodo59 »

surgical_fire wrote: post #169
andai wrote: post #148

The recently announced they're raising their prices 10x right? Which would put them... exactly where everyone else is on this graph. Edit: I seem to have misunderstood the news. I thought the magical cache read pricing was going away (0.002) and they were going to be on par with everyone else (0.02). But I have no idea. Edit 2: Apparently, neither do they! >We plan to raise the overall pricing for DeepSeek API servic…

> The recently announced they're raising their prices 10x right? No. They sent an email to customers saying that they will raise prices "significantly". How much that will be is speculation. My guess is that they will just remove the 75% discount they gave when they released V4 preview. It will still be relatively cheap even at 4x the current price.

It will be comparable to Luna then.

Re: DeepSeek V4 Flash 0731

#239

Post by lcampbell »

apitman wrote: post #211
ak_t wrote: post #164

Note this is the 07/31 release of DSv4 flash and not the "preview" that they put out a couple months or so ago. I've been running this model locally for a week, and the preview version before that. This updated one feels like a whole tier up. It's very capable for debugging and analyzing documents/data I upload. The killer feature, IMO, is the speed. On 2x RTX Pro 6000 Blackwell, its ~8k tok/s prefill and ~250 tok/s…

I'm getting like 25 tok/s on 2x RTX Pro 6000. This is with llama.cpp, but I had GPT tune it for me. I was under the impression vLLM was at most ~2x faster, and usually for highly parallel loads. Any tips on where I should look first for an obvious blunder? I'm guessing tensor parallelism or similar?

You're gonna want a custom vLLM build.

Here's a runbook: https://github.com/local-inference-lab/rtx6kpro/blob/master/...

If the newer builds aren't working, you might try running the old v6 build (based on the eldritch-enlightenment image). gilded-gnosis gave me some problems that I haven't bothered to track down, the old builds are still gonna blow away llama-server performance. And that's before you get hooked on vLLM's PagedAttention and can run multiple sequences without a ton of extra overhead.

Re: DeepSeek V4 Flash 0731

#240

Post by stavros »

alex0015 wrote: post #109
greenavocado wrote: post #96

Earlier quoted context omitted.

(1) you used opencode (2) what provider did you use. openrouter is trash because they shit up the model serving. no max effort and horrific cache utilization, on the order of 50-75%, absolutely garbage. beware

What should we be running deepseek on besides opencode? I chose it because I heard good things. Also provider is directly through deepseek credits.

I use the Deepseek API and pay peanuts. Very satisfied.
Post reply on HN