Custom code boosts Qwen3-30B-A3B inference speed by 50% on consumer GPUs

A developer has created custom CUDA and C++ code that significantly boosts the inference speed of the Qwen3-30B-A3B model on consumer hardware. Running at float 8 precision on an RTX 5060 Ti with 16GB of VRAM, the new code achieves 50-54 tokens per second, a 50% improvement over existing solutions like llama.cpp. This advancement enables more private, cost-effective, and environmentally friendly local AI inference. AI

IMPACT Enables faster and more accessible local AI inference on consumer hardware, promoting privacy and cost savings.

RANK_REASON Developer-created optimization for running an existing LLM on consumer hardware.

Read on r/LocalLLaMA →

• llama.cpp
• Qwen3 30B
• RTX 5060 Ti
• SGCB

• infra
• product

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →