[lambda]

I use Vulkan mostly instead of ROCm. Vulkan is actually a bit faster, paradoxically. I do switch out and try them both out, and it's not a huge difference, but I've been mostly saying on Vulkan.

The re-processing context every turn problem is definitely something I've hit. Some of the causes have been solved upstream in llama.cpp; make sure you're up to date.

But another cause of the issue that has a big effect is that older Qwen models didn't support preserving thinking. This means that each time you have a long sequence of tool calls with interleaved thinkging, as soon as you had your next turn in the chat, it would have to re-process all of that as it would drop all of the reasoning.

Qwen 3.6, however, now supports preserving thinking. This can use a bit more context, becasue you're not dropping the thinking every turn, but it re-uses the cache better, not causing you to have to reprocess a whole turn at a time each time.

In my models.ini, I have this for the Qwen3.6 models:

  chat-template-kwargs = {"preserve_thinking": true}

There are still occasional issues I hit where it will have to re-process, but getting up to date and enabling preserve_thinking has helped a ton.

[ndom91]

+1 using llama.cpp Vulkan releases with the Qwen models - runs much better than the ROCm releases.

I'll have to give the preserve_thinking a shot.

[jderekw]

Thanks for sharing have been running ROCm primarily with Qwen 3.6 and Qwen Coder, on the runs much better statement is that a stability, performance or other capability your experiencing?

[thefroh]

I'm a little surprised that preserve_thinking would matter here for cache purposes. for actual capabilities/intelligence, yes, I'd imagine it helps to have past reasoning traces in multi-turn setups.

but for caching, all you are doing is leaving off a fraction of the most recent assistant message generation, which will have little/no impact on cache hit rate.

[stymaar]

> all you are doing is leaving off a fraction of the most recent assistant message generation

True, but not a tiny fraction, qwen is very verbose in its thinking traces. And it basically means that for every (nonthinking) generated token you have to compute the KV twice (once as tg, the second one as pp).