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// 77d agoNEWS
llama.cpp Qwen3.5 slowdown sparks debate
A Reddit discussion in r/LocalLLaMA claims Qwen 3.5 models run much slower than expected in llama.cpp and llama-server, with the poster blaming recent implementation choices for the drop. The post offers no rigorous benchmark data, but it highlights a real pain point for local AI developers when new model architectures outpace inference-engine optimizations.
// ANALYSIS
This looks more like an early community signal than a confirmed regression, but it is exactly the kind of complaint open-source inference stacks need to investigate fast.
- –llama.cpp is explicitly built around high-performance local inference, so any sustained Qwen 3.5 slowdown would matter to developers serving models through `llama-server`
- –The Reddit thread is anecdotal and speculative, with no controlled tokens-per-second benchmark or reproducible test setup
- –The most plausible explanation is optimization lag for a newer Qwen architecture, not proof of intentional throttling or a broken release
- –For practitioners, the next step is straightforward: compare Qwen 3 vs. Qwen 3.5 under identical hardware, quantization, and default parameters before calling it a true regression
// TAGS
llama-cppqwen-3.5llminferenceopen-sourcebenchmark
DISCOVERED
77d ago
2026-03-10
PUBLISHED
81d ago
2026-03-07
RELEVANCE
7/ 10
AUTHOR
el-rey-del-estiercol