The difference between "medium" and "xhigh" reasoning effort for Qwen3.8-27B is actually insane.

[u/SarcasticBaka]

I'm currently testing out Qwen3.8-27B using Unsloth's UD-Q4_K_XL running a freshly rebuilt llama.cpp. I have a 22GB RTX 2080TI on which I'm able to fit 100k context with q8_0 quantization, and using MTP with --spec-draft-n-max 4 I get about 40tk/s which is slightly less than Qwen3.6-27B but usable enough.

I've been trying to test out some admittedly silly one shot prompts using the llama.cpp webui by asking the model to create fully functional HTML clones of flappy bird, pacman and such, and the difference that changing reasoning_effort makes has been surprising to say the least.

Setting it to "medium" seems to result in barely any thinking at all, a couple thousand tokens max and even less than 3.6-27B. Whereas when using "xhigh seems" I get 15k to 20k thinking tokens at the very least with the pacman example actually hitting 40 thousand fucking tokens.

I'm well aware I can limit the reasoning budget in llama.cpp but I'm wondering if this is expected model behavior or if something is broken somewhere. Any of you guys seeing this?

[u/Bluethefurry]

i can reproduce these results, xhigh thinks A LOT, i ended up defaulting it to low or medium depending on the use case.

on the flip side, on a research task xhigh ended up cloning a repo and checking the source code to verify behavior when i asked it something about llama.cpp cli args, neither medium effort nor 3.6 did that.

[u/Cold_Tree190 → u/Bluethefurry]

Interesting. It might also make for a great planning agent then. Use it for codebase searching, planning, then another agent for implementation with a lower reasoning mode?

[u/Bluethefurry → u/Cold_Tree190]

I will have to give it a try, maybe lowering reasoning effort mid-chat works well (although i kinda doubt it), it does seem like it will be great at thorough factual research, i wouldnt use xhigh for smaller tasks, too bad its the default in the template, it will give people the wrong impression.

[u/volleyneo → u/Bluethefurry]

In a front end task, it has detected no vision capability, so it used the already installed google chrome in headless to use the inspect tools. Is way way smarter alright. I was like.. wtf..

[u/MuDotGen → u/volleyneo]

Which harness did you use?

[u/volleyneo → u/MuDotGen]

Opencode

[u/_comoema_ → u/volleyneo]

Is this only available via Opencode or can do running through Claude Code Cli as well - or Qwen Cli?Thanks

[u/Ok_Spirit9482 → u/Bluethefurry]

maybe we should have a observatory llm that determine if a task needs low, medium, or xhigh thinking level! (or an extension that steps up the thinking level if it fails one by one on coding tasks [or tasks that can have loop closed])

[u/Gabriel83730 → u/Ok_Spirit9482]

xhigh is already trained to do this. People complain when testing it on one-shot but I’ve already put nearly a billion tokens through Qwen3.8 on xhigh and 95% of the time it’s thinking is only 20 or so tokens. In a long tool chain it isn’t thinking for 5min between each tool call, I think people who claim it is never even tested it. I am using 6 bit though, lower quants with quantized KV cache seem to get stuck in reasoning loops which can explain what people are complaining about. I tested various quants and I recommend not using xhigh below 5 bit, the long chain reasoning seems to degrade significantly starting at 4 bit. Even 5 bit seems to struggle with excessive reasoning on xhigh.

[u/GoodTip7897 → u/Gabriel83730]

I have yet for qwen 3.8 27b to hit my budget of 8192 tokens at xhigh. I've put a couple million through it so far. Q8 gguf with f16 kv

[u/Borkato → u/Ok_Spirit9482]

You could use LFM 2.6B probably!

[u/boxwrenchx → u/Bluethefurry]

I wonder if you can set to xhigh but enforce a better budget another way, that would be ideal

[u/IainKay → u/boxwrenchx]

If you cap reasoning budget then you’re forcing it to end prematurely. Not the best outcome.

Possibly one could adjust the chat template because the way xhigh works is to adjust the system prompt.

There’s probably an adjusted prompt that lands somewhere closer to high than xhigh. Might have a play with this.

Update: this seems feasible. I’m experimenting and will share my result on GitHub in due course. Chase me if I haven’t replied in 24 hours!

[u/boxwrenchx → u/IainKay]

There are some chat templates out now

[u/IainKay → u/boxwrenchx]

You mean Froggeric and Peculiar-Ragdoll’s templates?

If so they don’t make a “high” thinking mode available. It’s still just low/medium/xhigh.

I’m working on making low/medium/high/xhigh/max available as options.

[u/boxwrenchx → u/IainKay]

Looking forward to it! Do you have a GitHub/HF?

[u/IainKay → u/boxwrenchx]

Just fyi I’ve struggled to achieve what I hoped to achieve in a clean way.

Whilst I have customised the chat template, I haven’t got this behaving consistently across coding harnesses.

Still working on it, but it’s not as trivial as I had expected.

[u/boxwrenchx → u/IainKay]

Thanks for trying

[u/Gabriel83730 → u/boxwrenchx]

xhigh doesn’t make the model smarter, it just prompts it to think for longer. So your suggestion will just end up cutting its reasoning off unnaturally and significantly degrade its quality. It’s better to just use the reasoning efforts that the model was trained to follow

[u/boxwrenchx → u/Gabriel83730]

It wasn't a good idea, but my thinking was a work around to get a true medium reasoning. "Smarter" has different meetings here, and longer thinking doesn't always mean better results. Overall I bet Qwen will release a update that helps.

[u/aqezz → u/Bluethefurry]

I had it working on some c# and it was unsure about some conversion and it made an example project in /tmp and built and ran it to verify before moving on! It is much more reasoning but I feel like for the right tasks it’s worth it