2 ms·

The big problem with overthinking on a dense model is obviously the speed hit you take. Going from Qwen 35BA3B to 27B for me is about 7-8x slower (should be ~9x

by andy99 1mo ago

The big problem with overthinking on a dense model is obviously the speed hit you take. Going from Qwen 35BA3B to 27B for me is about 7-8x slower (should be ~9x?). This makes me a lot less patient for useless thinking tokens. I’d want to compare this to the new Muse 30B model which is super terse and has a whole different way of thinking (no “Wait,”) and in my experiments was way more token efficient to the point that the absolute tok / s didn’t really matter.

simonw 1mo ago
Comparing with Muse Glimmer is a good idea. I ran the same exact HTML tool generating prompt against both Glimmer 30B and Qwen 3.8 27B. Results: Qwen: https://gist.github.com/simonw/121ad098860028b2fab603fa12da1fd9 https://gist.github.com/simonw/121ad098860028b2fab603fa12da1... - 17,576 reasoning tokens, produced this HTML result: https://static.simonwillison.net/static/2026/qwen-over-thinking-bbox.html https://static.simonwillison.net/static/2026/qwen-over-think... Glimmer: https://gist.github.com/simonw/51e8ddb2ee597a5005fa63bd4927dbf0 https://gist.github.com/simonw/51e8ddb2ee597a5005fa63bd4927d... 1,021 reasoning tokens, this HTML: https://static.simonwillison.net/static/2026/glimmer-bbox.html https://static.simonwillison.net/static/2026/glimmer-bbox.ht... - ugly but functional. In both cases paste in the URL https://static.simonwillison.net/static/2026/two-pelicans-on-rocks.jpg https://static.simonwillison.net/static/2026/two-pelicans-on... to see them work. Both applications work correctly and fulfill the requirements. The Qwen one (which used the default xhigh reasoning setting) is massively over-engineered. The Glimmer one used whatever their default in LM Studio is and I would argue is a tiny bit under-engineered. Weirdly the Glimmer one doesn't work with images on other domains like https://static.inaturalist.org/photos/714731804/large.jpg https://static.inaturalist.org/photos/714731804/large.jpg - it fails with a CORS error, but you don't need CORS to load images and detect their width and height, and the Qwen one handles that URL just fine. That's because Glimmer added this unnecessary line: img.crossOrigin = 'anonymous';
- NitpickLawyer 1mo ago
  Yesterday I tried both as well. I do a quick "explain this repo" + "any security issues" convo to do a "vibe check" on the models and make sure everything works w/ serving and harness. Both qwen and glimmer explained it pretty well, and both accepted the security question without any issues, flagged a few things left there on purpose (hardcoded tokens, single auth, no logs, etc). I like the style of glimmer more. Much terser language, no adjectives, no fluffy claude-like language. ("Images are written to...", "Tasks are stored in SQLite...", "Docker image is built from ...") In contrast, qwen is a bit more flowery. ("Unbounded image processing / resource exhaustion — preprocess() opens whatever was downloaded with no size/dimension/format validation before the VAE encodes it..." , "SQLite as a queue — fine at this scale, but...", "Debug info leakage — exceptions are re-raised as...". But both flagged pretty much the same stuff, just ordered / styled differently. Mighty impressive understanding for a thing that I can run locally. Qwen served in fp8 w/ full kv cache, glimmer in w4a16 (the fp8 weights wouldn't serve for whatever reason), both at full supported context in 48GB of VRAM.
bogzz 1mo ago
I love reading Glimmer's "thoughts". Why use many word when few do trick?
- dofm 1mo ago
  It’s also a little bit snarky, almost. The stuff it thought during the car wash puzzle made me laugh.
  - shifto 1mo ago
    It wouldn't accept it was the Glimmer model and I had to stop when I realized I was arguing with my GPU. Was a surreal moment, lol.
- Gracana 1mo ago
  I’ve noticed dsv4 do that as well, but inconsistently. I thought it was broken at first, but no, it’s just kind of shorthand that it does while thinking.
- bblb 1mo ago
  Me machine, no human. Why waste token. Do fast, deliver.
lostmsu 1mo ago
Glimmer is stupider than 3.6 27B. You can't compare its speed to 3.8 and be done.

by andy99 1mo ago

simonw 1mo ago

Comparing with Muse Glimmer is a good idea. I ran the same exact HTML tool generating prompt against both Glimmer 30B and Qwen 3.8 27B. Results: Qwen: https://gist.github.com/simonw/121ad098860028b2fab603fa12da1fd9 https://gist.github.com/simonw/121ad098860028b2fab603fa12da1... - 17,576 reasoning tokens, produced this HTML result: https://static.simonwillison.net/static/2026/qwen-over-thinking-bbox.html https://static.simonwillison.net/static/2026/qwen-over-think... Glimmer: https://gist.github.com/simonw/51e8ddb2ee597a5005fa63bd4927dbf0 https://gist.github.com/simonw/51e8ddb2ee597a5005fa63bd4927d... 1,021 reasoning tokens, this HTML: https://static.simonwillison.net/static/2026/glimmer-bbox.html https://static.simonwillison.net/static/2026/glimmer-bbox.ht... - ugly but functional. In both cases paste in the URL https://static.simonwillison.net/static/2026/two-pelicans-on-rocks.jpg https://static.simonwillison.net/static/2026/two-pelicans-on... to see them work. Both applications work correctly and fulfill the requirements. The Qwen one (which used the default xhigh reasoning setting) is massively over-engineered. The Glimmer one used whatever their default in LM Studio is and I would argue is a tiny bit under-engineered. Weirdly the Glimmer one doesn't work with images on other domains like https://static.inaturalist.org/photos/714731804/large.jpg https://static.inaturalist.org/photos/714731804/large.jpg - it fails with a CORS error, but you don't need CORS to load images and detect their width and height, and the Qwen one handles that URL just fine. That's because Glimmer added this unnecessary line: img.crossOrigin = 'anonymous';

NitpickLawyer 1mo ago
Yesterday I tried both as well. I do a quick "explain this repo" + "any security issues" convo to do a "vibe check" on the models and make sure everything works w/ serving and harness. Both qwen and glimmer explained it pretty well, and both accepted the security question without any issues, flagged a few things left there on purpose (hardcoded tokens, single auth, no logs, etc). I like the style of glimmer more. Much terser language, no adjectives, no fluffy claude-like language. ("Images are written to...", "Tasks are stored in SQLite...", "Docker image is built from ...") In contrast, qwen is a bit more flowery. ("Unbounded image processing / resource exhaustion — preprocess() opens whatever was downloaded with no size/dimension/format validation before the VAE encodes it..." , "SQLite as a queue — fine at this scale, but...", "Debug info leakage — exceptions are re-raised as...". But both flagged pretty much the same stuff, just ordered / styled differently. Mighty impressive understanding for a thing that I can run locally. Qwen served in fp8 w/ full kv cache, glimmer in w4a16 (the fp8 weights wouldn't serve for whatever reason), both at full supported context in 48GB of VRAM.

bogzz 1mo ago

I love reading Glimmer's "thoughts". Why use many word when few do trick?

dofm 1mo ago
It’s also a little bit snarky, almost. The stuff it thought during the car wash puzzle made me laugh.
- shifto 1mo ago
  It wouldn't accept it was the Glimmer model and I had to stop when I realized I was arguing with my GPU. Was a surreal moment, lol.
Gracana 1mo ago
I’ve noticed dsv4 do that as well, but inconsistently. I thought it was broken at first, but no, it’s just kind of shorthand that it does while thinking.
bblb 1mo ago
Me machine, no human. Why waste token. Do fast, deliver.

lostmsu 1mo ago

Glimmer is stupider than 3.6 27B. You can't compare its speed to 3.8 and be done.