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  • Hacker News
  • Very promising. So it will both keep the speed and reduced price, yet exceed performance of the quite sufficient deepseek-v4-pro?

    Should be extending the lead in intelligence/cost index, as deepseek-v4-flash already were the most price efficient model, which now becomes even better. Although, in the deepseek APIs, the cost is leaking all information about codebases to China.

  • Supposedly better than GLM 5.2 according to at least one benchmark.
  • For both US and China models - what standard security checks and QaQc are you all doing? We're running small gamuts to test for unsolicited jailbreaks (model jailbreaks you) and incorrect records (Fake Accuracy - as Easter Egg or common thread) meaning falsified logic or information cooked in by the developers, rather than the training data speaking for itself
  • What was preventing them from calling it v4.1-Flash to distinguish it better?
  • It went from "ds v4 preview" to "ds v4". That's enough of a distinction.
  • Sounds like it'll replace v4-flash, v4.1 would be nice to keep both available. On the other hand, it's nice to just get an improvement on anything that asks for "deepseek-v4-flash" without having to change the model string.
  • Kimi K3 (instead of Opus) for expensive stuff, DSV4 Flash for tasks (instead of Sonnet)?

    Does this make sense?

  • it does! I'm always amazed when I use DSV4 flash for coding or server checks and after an hour of working with it my (pure api call) balance is about 30 cents
  • Looks like they will release an updated version of deepseek-v4-pro soon, which most likely will beat kimi k3 at both intelligence and cost (judging by the vast improvements to dsv4 flash)
  • Deepseek and moonshot are the only two providers I consent to training for.
  • Xi going to shut down open-weighting of them in a matter of months. No one seriously doubts this. They will be too powerful and they will be gone.
  • CCP will be happy! Go on and share all your data with them..
  • Why not also Qwen?
  • Woah, a 200B model competing with GLM-5.2 and getting close to Opus 4.8. Quite impressive.

    If those numbers translate well to its general capabilities, with the great caching DeepSeek has, I feel like this model will get tons of usage.

    by ggcr
  • MiniMax's another lab that's known for relatively smaller models (their latest, M3 is 295b) that punch way above its weight.
  • Not just 200B model, it is only 160GiB.
  • If the benchmarks are real and reflect actual use, then this is an insane model. This 300B model outperforms the previous DS4 Pro preview model (1.8T params), and it looks like it outperforms GPT 5.6 Luna too. And it's still cheaper than Luna, even with the price decrease.

    Crazy.

  • On DeepSWE Deepseek is 54.4% and Luna is 67%
    by cbg0
  • OpenAI must've known this was coming, hence the Luna price drop. This competition is amazing!
  • Essentially I'm running everything on flash now inside pi. With the correct set of MCP servers, context reducer tooling and skills it can implement any task I throw at it. Some sessions take 30+ turns, but it's fast and cheap; all this in an hour, with ~$0.5 cost.

    (TBH though, in my multi-subagent workflow I do use other, more expensive models for planning, reviewing, oracle-ing)

    I haven't used our slow opus subscription for weeks.

    (Also set up an OpenWebUi self-hosted chat that works from my phone, has some mcp and skills. fully replaced perplexity. Monthly cost ~$18 for hosting and subscriptions)

  • How can one set topp and temperature in pi?
  • Do you notice any improvements with this update?
  • Do you have any recommendations of such extensions for pi?
  • I want to second this, I use the same setup (pi + deepseek, with lots of custom tools for tracking TODOs, doing things with less tokens, etc, and with a SOTA model for very difficult tasks) and it's all I need it to be.
  • I use deepseek for a lot of my personal day-to-day agent needs, and I will simply put this here and let this speak for itself, last 30 days:

    - Cost: $4.55USD

    - API requests: 3,467

    - Tokens: 323,183,886

    And as an engineer who leads a small team, I have very high standards for quality, and these carry across to my personal projects where I use deepseek. It has not disappointed at all for coding or review tasks. For everything else, use another model.

  • OpenRouter?
  • What are the tasks where it falls short?
  • What harness are you using to achieve that level of token caching?
  • You are using DeepSeek's services directly? Doesn't that end up sending at least snippets/chunks of code to a server where it is subject to Chinese government data access laws? Even if I was okay with that, my organization would never be. And even if they were, our partners/vendors/customers would not be. I think that's the sticking point for a lot of people.