llama.cpp Memory Inefficiency with Qwen Context? User Reports
nullc · reddit · 2026-08-14
A user finds llama.cpp is significantly less memory-efficient for Qwen architecture compared to muse glimmer on the same hardware: glimmer supports 24x128k contexts, while Qwen only 3x256k or 6x128k. Despite architectural analysis suggesting Qwen's per-token state is smaller, actual performance is worse, indicating a potential memory inefficiency in llama.cpp for Qwen, impacting batched performance.
More from Infra
- Three CoreWeave co-founders have sold $3.3B in shares since IPO amid credit worries — SumitGup · 2026-10-16
- Cherry pi on a Raspberry Pi: the tiny-model rumor developers are watching — sull · 2026-10-16
- CoreWeave's debt costs falling: DDTL spreads tightened from S+9.62% to S+2.25% — BenBajarin · 2026-10-16
- SoftBank lines up US IPOs for SB Energy and AI robotics spinoff Roze, valuations top $50B — nordicinst · 2026-10-16
- TRL reproduces Modal's mixed-precision async RL: plain GRPO collapses, SC+MIS holds 0.72 — QGallouedec · 2026-10-16
- Hugging Face scales Indic pretraining with 2.8T tokens and an open data pipeline — Hugging Face Blog · 2026-10-16