Qwen 3.6 model hits 110 tokens/sec on consumer GPUs via llama.cpp

The open-weight model Qwen 3.6, in its 35 billion parameter version, has achieved an impressive 110 tokens per second inference speed on consumer GPUs with 12GB of VRAM. This performance was enabled by a specialized variant of llama.cpp, referred to as ik_llama.cpp, and specific quantization techniques. Additionally, a 27 billion parameter version of Qwen 3.6 has been successfully deployed locally using llama.cpp's server configuration, providing a practical example for self-hosted AI applications. AI

影响 Accelerates the accessibility and practicality of running powerful LLMs on local hardware, reducing reliance on cloud services.

排序理由 The cluster details benchmark results and practical deployment examples for open-weight models on consumer hardware, focusing on performance optimizations. [lever_c_demoted from research: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

• Claude Code
• consumer GPUs
• GitHub Copilot
• ik_llama.cpp
• llama.cpp
• Qwen 3.6
• Pi

• 模型发布
• 基础设施

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