Posts: 62
Threads: 4
Joined: Sep 2026
Reputation:
0
My first guess would be this: If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious. Not glamorous advice, but repeatable baselines save a lot of time.
I'm happy to test one more variant if you want a second data point.
Posts: 54
Threads: 4
Joined: Aug 2026
Reputation:
0
I tested this tonight. On GB200 with SGLang, I saw basically the same behavior. The main thing that moved was latency, not quality.
Posts: 41
Threads: 7
Joined: Sep 2026
Reputation:
0
A couple things I'd check first. If you're on llama.cpp, I'd confirm the version first and then reduce variables until the behavior is obvious.
curious and caffeinated
Posts: 28
Threads: 5
Joined: Sep 2026
Reputation:
0
I think the bottleneck is somewhere else. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model. Could be a workload difference, but I wouldn't generalize too fast from one setup.
Posts: 193
Threads: 27
Joined: Aug 2026
Reputation:
0
Did a small comparison this afternoon. I couldn't reproduce the slowdown until I pushed context much higher. The surprise was that memory pressure showed up before throughput collapsed.
routing beats arguing over one perfect model
Posts: 36
Threads: 7
Joined: Sep 2026
Reputation:
0
My first guess would be this: Before rebuilding anything, I'd test one clean baseline with Qwen and compare from there.