It’s maybe a bit interesting that Jetbrains are making moves to integrate with local models more closely, but I think claiming this is “easier” is incorrect for most users.
The company also said that it chose Qwen3.6 over the newer Qwen3.8 (released earlier this month) because the latter runs slower on "today's Macs" since it needs reasoning enabled.
They’re also targeting 64GB M5 Pro and up as “today’s Macs” which perform fine with reasoning enabled.
Sad a Qwen3.8-35B-A3B model wasn't released.
Also, I think this is just an ad.
I'm not sure what that means on a M5 max, definitely faster, I don't know if it really plays into the strengths of the new chip design though.
brew install llama.cpp
llama serve -hf unsloth/Qwen3.6-35B-A3B-GGUF:UD-Q4_K_M
open http://127.0.0.1:8080I’m using Goose but have tested Codex and OpenClaw among others. Codex worked fine but I couldn’t get web search to work with Qwen. OpenClaw I could get web search to work but its system prompt eats a lot of context tokens. Goose works for web search if you use SearchXNG, and has fairly slim system prompts. I’m still evaluating DeepSeek Harness and might move to that once it’s more stable. I tried other more obscure options but they had some flaws that made me settle on goose.