2 points | by bhamm-lab 4 hours ago ago
1 comments
Wrote up some notes from upgrading my local llama.cpp setup on AMD Strix Halo hardware and testing a batch of newer open models.
Main findings:
- Kimi Linear 48B works well as a generalist on my hardware (fast, consistent).
- Qwen3 Coder Next is my new default for coding tasks.
- Aggressive quants (Q2_K_XL) on massive models (200B+) can still be useful for long-running/background tasks, even if they aren't interactive.
Happy to answer questions about the dual AI Max+ 395 setup or how I run models in kubernetes.
Wrote up some notes from upgrading my local llama.cpp setup on AMD Strix Halo hardware and testing a batch of newer open models.
Main findings:
- Kimi Linear 48B works well as a generalist on my hardware (fast, consistent).
- Qwen3 Coder Next is my new default for coding tasks.
- Aggressive quants (Q2_K_XL) on massive models (200B+) can still be useful for long-running/background tasks, even if they aren't interactive.
Happy to answer questions about the dual AI Max+ 395 setup or how I run models in kubernetes.