Thread

1. Gareth321 · 1790064431 · focus · HN ↗

   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.

   1. abalashov · 1790119028 · focus · HN ↗

      Welcome to the dark side. I've been on Kimi, with a little DeepSeek-V4-Pro, GLM 5.2/5.3, and MiMo thrown in, for probably about a year now. It's great here!

      For DeepSeek, I recommend their Reasonix harness strongly, due to its alignment to DeepSeek's prefix cache. It means mostly (95%+) cache hit input tokens, so very cheap large-scale code analyses and things that require mega context windows (at the cost of some attentional drift, yes). Reasonix does require that you send data to China.

      For most everyday stuff outside of where Reasonix + DeepSeek just makes overwhelming sense, I use OpenCode/Maki/Pi/whatever harness I feel like using today with Kimi K3, via OpenRouter. This does not require sending data to China.

      I also use Kimi K3 in Zed via OpenRouter quite a bit, but sometimes like to mix it up with the other models.

      For local hardware experiments on my MacBook (128 GB unified memory), Qwen3.6-35B-A3B (speed) and Qwen3.8-27B (intelligence, but slow). As has been widely noted, this amount of unified memory isn't as useful as it seems, due to memory bandwidth and decoding constraints, lack of tensor cores (on the M4 Max, anyway), etc. A giant bag of memory isn't fast, but it'll let you load some impressively big models. The future M5 Studio Macs will continue in this general vein, but will of course be somewhat faster, particularly due to the apparition of tensor cores in the M5 -- Neural whateverApplecallsthem.

      The Chinese models are simply _excellent_, and cater to lots of use-cases and tastes.

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