Qwen3.5-2B Compiled into qwenGPU with 45 CUDA Layers
Original title: Meet qwenGPU: Qwen3.5-2B With 45 Compiled GPU Layers That Run CUDA
The small model now runs 45 layers natively on GPU using CUDA.
Researchers compiled Qwen3.5-2B weights into qwenGPU, enabling 45 layers to execute directly on CUDA hardware. This optimization allows the 2B-parameter model to run efficiently without extra overhead on supported GPUs. The release focuses on practical deployment of the Qwen3.5 series.
- 45 layers compiled for direct CUDA execution
- Qwen3.5-2B optimized for GPU
- Small-parameter model achieves native CUDA performance
- Compiled weights enable immediate GPU inference
- Vendors
- Alibaba
- Products
- qwenGPU
- AI models
- qwen3-5-2b
From the original article
14 min read at marktechpost.comqwenGPU compiles a 4-lane SIMT GPU into Qwen3. 5-2B as 45 untrained layers. The model writes every step of real CUDA launches itself, using Gated DeltaNet state as registers and memory.
By Michal Sutter · marktechpost.com
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