Running Qwen3 30B A3B at 50 tok/s on RTX 5060 Ti
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
| Experimented with some custom CUDA and C++ code that can now run a Qwen3-30B-A3B at 50-54 tok/s at float 8 on an RTX 5060 Ti with only 16 GB of VRAM. This speed is roughly 50% improvement to llama.cpp which runs at around 33-34 tok/s (with n-cpu-moe). These speedups come mostly from combining SOTA solutions I saw in papers in NeurIPS, ICML, and EuroSys Engines like these allow for new local inference oppurtunities on consumer hardware, offering more private, cheaper, and greener alternative to centralized datacenters! [link] [comments] |
More from r/LocalLLaMA
-
Uncensored Multi-Model Releases, LongCat-Flash-Lite-Sparse with MTPs and LSAs, Qwen3.8-27B with MTPs, Qwen3.5-122B-A10B with MTPs, Qwen3-Coder-Next and Laguna-S2.1 with Vision, All Available in GGUF Format! Bonus: Links to my llama.cpp Fork for LongCat-Flash-Lite Support and…
Aug 30
-
Got MiniMax H3 video generation running in TensorSharp
Aug 30
-
Qwen3.8-Flash-Next NVFP4 2xDGX Spark config: 50t/s decode, 2,900t/s prefill
Aug 30
-
Don't Sleep on EXL3 Quants
Aug 30
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.