Discussion summary

DeepSeek 4.1 Flash is not causing industry concern due to slow support, perceived as a community issue, and its niche status. Some users highlight its capabilities, while others mention limitations like hallucinations and pricing.

What the discussion says

  • Support for DeepSeek 4.1 Flash is slow and limited.
  • Some see it as a hidden gem with high speed and privacy.
  • Concerns about hallucinations and model stability.
  • Pricing and provider differences affect user experience.
“DeepSeek V4.1 Flash is a hidden gem, with speeds above 200 tokens/sec.”
— ne01
“It hallucinates a lot, but the architecture is a genuine move forward.”
— sotander

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  • Hacker News
  • I had the same experience using ds 4.1 last couple of weeks. It’s insanely good for the price. I’m doing mostly web dev it excels at everything I throw at it. The pricing is ridiculous. I canceled my gpt subscription and haven’t looked back hope the pricing stays like that. I almost never need a better model. I still keep my Claude 20$ sub for now but I feel like one more iteration and I won’t need even that anymore I hardly use it
  • I have a pretty large, complex project I've been building with heavy AI use (new language + compiler). I was following a 'strong model as orchestrator launching cheap models as implementers' pattern, but I recently trialled just using Deepseek-V4.1-Flash as the model for both layers because of the cost savings (with mimo v2.6 flash on code review agents for some decorrelation).

    I was previously using GLM-5.3 as the orchestrator, after switching to DS anecdotally there was an unnacceptable quality loss, mostly around not taking all the relevant context into account when making decisions, pulling new design out of thin air without discussion too often, and being way too wordy and rambly in documentation despite prompting to avoid it. There's a lot of docs, rulings, core concepts, design philosophy to uphold and DS was just not cutting it.

    However, it's perfectly capable of being the sole agent for all of my well specced implementation tasks. I've gone back to GLM as the orchestrator.

  • Because DeepSeek is not "a month or two" behind as claimed in the article.

    These open models still did not beat February's Mythos / Fable 5.

    DeepSeek 4.1 Flash is behind GPT 5.6 Sol, and that one is left in the dust by the excellent Opus 5.5.

    Rumors say Anthropic is holding in reserve the big improvement, Fable 5.5, for the IPO.

    It's plausible that open models are 6 - 12 months behind, and there is no "good enough". As long as progress doesn't slow down, leading labs have nothing to fear.

  • Oh man. v4.1-flash has been an sbolute game changer for us. We run all our Personal Assistants now on flash (thinking high) by default and it works incredibly well. There is really no need for basic agentic tasks that might require Kimi K.3 or GLM-5.3 levels.

    Once its gets juicier, we let flash launch specialized subagents with specific models. GLM-5.3 for coding or Kimi K.3 for research and critique.

    But as a main driver. I love flash. And it brought our bill down by A LOT :D

  • I have been using DeepSeek 4.1 flash intensively for over a month. If I run it all day long it costs $1-2. Its fast. Previously I was always quickly running up to my Claude/Codex 5 hour window (on the $20/month plan). The cost savings of DeepSeek is real as shown in this article and I am using subsidized plans.

    DeepSeek is horrible at grilling sessions (the /grill* skills to make technical decisions). It doesn't know how to explain things. Maybe the skill could be adjusted. It also doesn't come up with as good solutions as Opus/Sol.

    What I use it for is

      * the orchestator of my coding workflows
      * the tester/verifier of code changes
      * the sub agent that explores code or does web searches
      * putting together code base research reports
    
    Previously I planned with Opus/Sol/Astra and then I used DeepSeek for coding, and then reviewed with Opus/Sol/Astra. With the cost improvements to Opus/Sol I am trying to use them for coding instead now so there will be less back and forth review needed.

    They are all working together in Pi using the extension @tintinweb/pi-subagents where my workflow skill is calling different subagents that use different models.

    Luna is cost competitive, but doesn't score as well on intelligence. I do need the intelligence for most of what I use it for, so I am not motivated to use Luna. Haiku also doesn't seem like a competitive price/performance mix.

  • Marketing.

    Have you guys see how aggressive is the push for enterprise use by both OpenAI and Anthropic? I had friend from a non-tech industry in Asia telling me that their company was offered free trial of the enterprise version of Claude, with trainings and such.

    On the other hand, DS and Z.ai, have zero to none marketing outside China. There is friction to use DS/GlM models and the ZDR is unclear, so most enterprise that has heavy AI usage hasn't move over yet. They would rather spent $200 for the peace of mind than to take the risk of being slam as a national traitor down the road (which again is another form of marketing by Big AI, trying to frame Chinese models as thiefs).

    So, I don't think they are not freaking out, it's just that they are addressing different market segments and reacting to the situation differently.

  • I'm paying for the heavily-discounted subscriptions, not the API rates. There isn't really a cost gap for me. DeepSeek doesn't have a subscription to compare to, but when I compared the GLM 5.3 usage I got from a $100/mo Z.ai subscription compared to Opus 5.5 on a $100/mo Claude subscription, there wasn't a big gap. And GLM 5.3 is very clearly not a frontier model (deepseek v4 seemed a lot closer, but I didn't use it enough to really say for my workloads).

    I don't think those subscriptions nave negative contribution margins, either. I think we're seeing a lot of price discrimination by the big labs, and huge margins on their frontier models. The fact that they have been cutting prices to their second-biggest tier of models (Opus/Sol).

    Open models catching up and collapsing these margins would worry me if I were a shareholder in the big labs, but as a user, I really doubt that the western labs have bigger environmental impact just because they have higher API costs, I think they have a ton of efficiencies they aren't sharing with customers yet because demand is so high.

  • The reason people aren’t freaking out is because most people are using heavily subsidized subscriptions.

    I tried the cheapest provider on openrouter and burned through $50 in a few days. Quality was ok, seems slightly above Luna quality perhaps? But that $50 is 1/4 of my codex subscription where I could have burned that many tokens or more using Astra within my weekly reset.

    This won’t last forever but as long as the frontier labs are subsidizing this heavily the open models won’t matter.

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