Qwenputer explores a fascinating idea: embedding computational machinery directly into LLM weights, without retraining the original language model.
Developed by
@divagr1925 , the project has evolved from a RISC-V CPU inside Qwen3.5 into a family of models exploring new ways to extend LLM capabilities. The full model family and an interactive demo are now available on ModelScope:
๐ Explore all models:
๐งช Try the interactive demo:
Here's a closer look at the model family:
โข Qwenputer embeds a functional RISC-V CPU inside Qwen3.5, using Gated DeltaNet's recurrent state as RAM.
โข Qwenputer-Filesystem introduces persistent file storage within the model's recurrent state, enabling memory across sessions.
โข Qwenputer-NPU extends the internal CPU with neural network instructions, allowing it to execute small models.
โข QwenPU takes things further with a dedicated vector unit capable of running Karpathy's 260K-parameter Llama inside Qwen itself.
Original project ๐: