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Posted by bilsbie 4 hours ago

Qwen 3.8 27B is excellent, but it defaults to overthinking things(simonwillison.net)
101 points | 41 commentspage 2
cyanydeez 2 hours ago||
--thinking-budget and --thinking-message is all you need in llamacpp to keep it progressing.

the message can be some combination of tool calling, summarizing, etc. It's overthinking often is a bunch of recursion, so simply stopping t and redirecting is all you need to do.

If someones building a harness for llamacpp, you can set this per message, so it's possible to dynamically control it by watching for the expansion of the thinking traces, and redirecting it.

I use the message to tell it to use subagents, add additional logging and to use opencode's dynamic context pruning.

As such, we'll just whisper here _skill issue_.

dofm 2 hours ago||
Unfortunately in xhigh thinking it goes down rabbit holes in such an extreme depth-first way, that whenever you choose to cut it off, there is a very good chance it will not have got round to musing on even half of the prompt! It doesn’t really obviously loop in xhigh, so I am not sure if an “overthinking guard” proxy would have much to go on, but it does obsessively ruminate on edge cases. I have seen it overcomplicate simple code as a result even in my limited testing.

Probably the better solution if you want it to be quicker but still fairly thorough appears to be to configure reasoning effort instead of thinking budget. It seems to do very well still even on the Low setting; on the Medium setting it can get stuck in loops like 3.6 does.

I think xhigh reasoning effort was an absurd choice for a default, and so was not sorting out the chat template so LM Studio could offer the reasoning effort dropdown.

cyanydeez 2 hours ago||
to the point though: most of that overthinking is useless if you have a proper redirect message. So setting arbitrary budget and getting it a good message will do the trick regardless of what type of thinking it's doing. The reason thinking seems to work is that it's just trying to find an optimum outside the local optimum, and the thinking trace helps find it.

The only think I could think that'd be better than the --reasoning-budget would bet a budget jitter just in case it really is repeating a pattern and you want to escape it arbitrarily, otherwise yes, it could keep looping if you're always cutting at the wrong time.

dofm 2 hours ago||
> The reason thinking seems to work is that it's just trying to find an optimum outside the local optimum, and the thinking trace helps find it.

Yes, I think I finally have an intuitive sense for that. But surely on a longer prompt it is still better for the final response if the thinking has at least brushed past all of the prompt?

One of the things I witnessed with xhigh is that while the thinking trace starts out intending an overview of the prompt, it actually can go fully down a rabbit hole off one of the first two or three bullet points even when it was seemingly intending not to.

It’s basically a lot like me. Gets sidetracked by the interesting bits.

bitexploder 2 hours ago|||
Yeah, but be fair. Working with small models is a different ball game. Not all the batteries come included :)
bellowsgulch 2 hours ago||
This is definitely such a cool feature that I wish cloud providers would expose.
blagui 2 hours ago||
You have 4 thinking levels.

You can disable it. It's well known issue in Qwen, previous releases I would disable it by default.

Also xhigh seem a new thing.

dofm 1 hour ago|
Yes. Though the chat template doesn’t tell LM Studio to offer the little dropdown. You can bodge the template in the load parameters.

Unsloth Studio / Desktop has it working really well with their version of the weights.

deadcatfound 3 hours ago||
For agents, token efficiency is an operating cost. I’d rather have a terse model that escalates hard cases than one that overthinks every tool call.
kamranjon 2 hours ago||
A no-thinking pelican! I hope to see more, it's surprisingly good for just 2 minutes.
javchz 2 hours ago||
I wonder if this can be fixed with LORAs.
bitexploder 2 hours ago|
I had to fix this on 35B A3B -- I have a proxy that just shuts it down if it gets to 2K thinking tokens and injects something like "We have thought enough, let's begin working." and it almost always finishes the turn then. It rarely needs more than 2K thinking tokens and if it does there is always next turn. I would need to see what 27B is actually doing, but these smaller Qwen models seem prone to this.
dofm 1 hour ago|||
Unfortunately in xhigh reasoning effort it will burn through 2K tokens before it has even finished its bullet point overview. It really is intense and obsessive. You might need ten times more!

Your strategy would likely help in medium reasoning effort (because there it gets caught up in the very typical Qwen looping).

Not seen looping in the “low” reasoning effort mode.

bitexploder 58 minutes ago||
I have been using Muse Glimmer for a few days instead of A3B. It gets the job done quicker than A3B despite being several times slower.
logicallee 1 hour ago|||
>I had to fix this on 35B A3B -- I have a proxy that just shuts it down if it gets to 2K thinking tokens and injects something like "We have thought enough, let's begin working." and it almost always finishes the turn then.

that is amazing, thanks for sharing.

LoganDark 2 hours ago||
I hope Apple does end up moving to HBM. Unified memory has been a huge godsend, but the low memory bandwidth is just such a killer. Even/especially on M5, where the available compute is starting to starve incredibly badly on ML workloads.
dofm 1 hour ago|
AFAIK that is initially only for the iPhone?
LoganDark 1 hour ago||
Apple is reportedly considering skipping the higher-end M6 chips altogether, which could potentially give enough time for higher-end M7 (in over a year) to use HBM
kennywinker 11 minutes ago||
Considering, or being forced to consider due to the hardware crunch?
onSmallMessage 1 hour ago|
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