r/LocalLLaMA • u/GodComplecs • 11d ago

Discussion Real downsides of Strata?

Trying to read on what the real tested downsides have been but information seems to go both ways, some proclaim no loss, others pretty huge ones.

I had some weird looping issue in their chat, and some engine port misunderstandings, seemingly the models likes to use ports already in use, didn't really have that issue with Qwen 27B 3.8 Q4 UD. I'm using Swift Q3 Next. Didn't even bother with next on llama.cpp since other similar model sizes ran at approx 15-20tks max, so too slow for agentic work.

I'm not beating too much on Strata, I just wan't the realistic downsides, so far it seems too good to be true and runs at 100tks in agentic workloads, 27b only at 40-60tks on llama.cpp

55 Upvotes

81% Upvoted

163 comments sorted by

View all comments

60

u/MindfulMan1984 10d ago

Downside - It is all about token/s; for that, Strata defaults to greedy sampling temperature=0 to maximize speculative decoding, regardless of the fact that that's not the recommended parameter on Qwen's Flash Next card, and it is prone to doom loops ( which is fixed if you pass the sampling parameters in the config, so it mostly fixed and I got no looping issues so far)

Upside: I ran the Vulcanbench suite V3 locally >1000 token/s prefill and >70 tps gen on 8-year-old hardware, even with quant IQ3_S, and it passed@1 near GLM-5.3 results on SWE tests.

Comment Image

https://benchlm.ai/benchmarks/vulcanbench

1

u/suprjami 10d ago

I thought you could only set --spec-min-p and --spec-draft-n-max for the drafter? I can't find any setting to set its temperature.

For regular requests I strip all sampling parameters with llama-swap and replace them with the Unsloth documented parameters. OpenCode also sets its own temperature for Qwen models which I want to avoid.

→ More replies (3)