82 pointsby theanonymousone7 hours ago7 comments
  • Gareth3213 hours ago
    OpenAI usage limits have been severely cut, and intelligence appears to be markedly declining, so I'm going to start trying these Chinese models seriously now. I don't mind if it takes longer. I just need the intelligence to predictably work the same way from day to day.
    • unsupp0rted3 hours ago
      Same- I pay $200/mo for Codex but whereas I used to get a week's work out of a weekly limit, now I get roughly 1~2 days.

      I've stopped using Astra entirely and remain on Sol orchestrating Luna Xhigh, but it's still not nearly a week's usage for a week's allotment.

      And even then, whenever a new model is about to come out, it feels like the model I'm using is being dumbed down substantially.

      I have no evidence for this and can have no evidence for this, but I can vote with my wallet regardless.

      • Gareth3212 hours ago
        I strongly agree. Check out the Codex subreddit. Many empirical examples of Astra silently downgrading the models. One found Astra was silently using Luna Max (but still billing for Astra).

        Even when I try to stick with Sol X/High, my limits are at best half of what they were before Astra launched, and the intelligence has declined markedly.

        I cancelled my $100 plan. This is absolutely absurd and frankly unusable now.

        • Muromecan hour ago
          It feels bizarre reading about the amounts spent on it here and paying like 10 eurobucks a week for DS
          • f6v2 minutes ago
            For me, DS Pro is still behind Sol. But I do think many people hitting the Codex limits in 1 or 2 days are doing something wrong.
          • Gareth321an hour ago
            These tools were pretty great if you could afford them, but now they are expensive and shit, and that combination doesn't work.
    • loloisi27 minutes ago
      Sol 5.6 xhigh had been a very reliable workhorse for coding for me via the 200 bucks sub.

      But this week they seem to have tweaked the system to a point at which all models (Astra, Sol, Luna) hit rate limits all_the_time without me being anywhere close to the weekly limit.

      Early results with MiMo 2.6pro are quite encouraging for anything that's non-UI work so likely switching spend for the time being

    • phoghed33 minutes ago
      > and intelligence appears to be markedly declining

      Serious question: does anyone have evidence of this?

      It’s something that’s constantly asserted, and has been since 2023. Every time someone posts a site that tries to track this though, I look at it and it’s just a flat line.

  • tensegrist5 minutes ago
    where's the flash model? it's out already isn't it
  • egeres4 hours ago
    It feels suspicious that MiMo-V2.6 Pro gets 46 in de index while DeepSeek-V4.1 (https://artificialanalysis.ai/models/deepseek-v4-1-flash) gets 39. According to the appendix at the bottom of https://mimo.xiaomi.com/mimo-v2-6 the deepseek model sometimes surpasses mimo and it's not so far behind in capabilities. A week ago opus 5 appeared 1 points ahead of fable 5 despite fable being a much smarter model (this has been corrected already)
    • SyneRyder2 hours ago
      The main AA benchmark keeps changing, and had to be radically changed when Astra came out and showed zero improvement over GPT 5.6 Sol in their benchmark. Opus 5 is still 1 point ahead of Fable 5.0 on the index, if you manually add Fable 5.0 back into the list, so it hasn't actually been "corrected". It's only Fable 5.1 that is shown as ahead of Opus 5.

      The AA benchmark is a weighted average of other benchmarks and some internal ones. I think the difficult part is finding benchmarks that reflect your own use of the models.

      • seahorseemoji29 minutes ago
        The way Artificial Analysis keeps changing their weights feels kind of like deciding who the winner should be and making the weights reflect that. They’ve been changing their weights to add more weight to improved long-running agentic capabilities, but doing so means they’re reducing the relative importance of world knowledge and of writing ability.

        I’ll grant that maybe world knowledge isn’t that important for these models. But writing ability is important for human understanding, and I think the weird turns of phrase and word choices reflect the labs’ underweighting of the importance of human understanding.

    • GodelNumbering2 hours ago
      > It feels suspicious that MiMo-V2.6 Pro gets 46 in de index while DeepSeek-V4.1 gets 39.

      Why?

  • dom964 hours ago
    It is an impressive model. Agreed on most that is written on this page, with the exception of it being fast. I ran it on my own LLM benchmark suite[1] and it is faster than DeepSeek but still much slower than leading models. But it's pricing is where it really shines.

    KillSwitch-Bench 1.0

      Claude Opus 5           66.9
      GPT-6 Astra             57.9
      Claude Fable 5.1        46.7
      MiMo-V2.6-Pro           38.8
      Muse Spark 1.3          36.5
    
    1 - https://bench.killswitch-lang.org/
    • ricardobeat25 minutes ago
      Speed seems to vary a lot with demand. Last night it was reaching 80+ tok/s
  • ignoramous2 hours ago
    Per Xiaomi, MiMo v2.6 training run cost $3.47m. A far cry from the estimated costs ($100m+) for the Big 5 (MSL, xAI, GDM, OAI, Ant). I wouldn't be surprised if salaries and R&D costs have similar drastic disparities.

    For a model that matches Muse Spark 1.3 in benchmarks, MiMo v2.6 Pro is incredibly cheap, given its cache rates will remain $0.0036 per million.

    • imjonse2 hours ago
      That is the RL training cost only. Their announcement blog mentions this: https://mimo.xiaomi.com/mimo-v2-6#scaling-rl-fully-open-sour...
    • drbscl2 hours ago
      My understanding of tech salaries in China is that they are pretty decent, but not as high as in SF; closer to typical European salaries.

      Mostly due to lower cost of living; Shenzhen is way cheaper than SV

      • f6va few seconds ago
        I seriously doubt salaries are included. It must be just the electricity and GPU costs.
    • NortySpock2 hours ago
      I sorta got the impression that the $3.47 million only covered post-training , given that few of the graphs start at zero. Is a barely-trained model going to score 48 on DeepSWE v1.1 ?

      https://mimo.xiaomi.com/rl/

  • jampekka5 hours ago
    "When evaluating the Intelligence Index, it generated 140M tokens, which is somewhat verbose in comparison to the median of 140M."
  • kosolam4 hours ago
    Why sol is not in the comparison?
    • guelo2 hours ago
      the graph has a dropdown for selecting models
      • kosolaman hour ago
        Not on mobile unfortunately
        • guelo33 minutes ago
          Not the graph at the top, the one further down.