Leaks and public signals point to upcoming Qwen4 models up to 120B while Qwen confirms its 4.0 and 5.0 series will remain open source. Community experiments from QwenPU to local deployments keep the model family central in the self-hosted scene.
An anecdotal report about a Q4 model running with llama.cpp on an RTX 4090 reopens the reproducibility problem in self-hosted deployments: without hashes and pinned versions, local control remains incomplete.
A pull request in the QwenLM/qwen-code repository shows unannounced model IDs: qwen4-max, qwen4-coder-plus, and qwen4-omni-120b-think, all resolving to a 262,144-token context window. The omni fixture detail confirms the models are not hypothetical, ...
Qwen's head Liu Dayi Heng has denied rumors that future Qwen series would move to API-only releases: Qwen 4.0 and 5.0 will remain open source. With 3 billion downloads, over 460 models, and 300,000 derivatives, the decision strengthens a strategic ec...
A researcher compiled an NPU into Qwen 3.5-4B weights and ran stories260k without external runtimes. QwenPU redefines the boundary between model and platform: weights become a computational substrate, with implications for self-hosted deployment, aud...
QwenPU compiles an NPU into Qwen 3.5-4B's weights to run Karpathy's stories260k, with no external tools and bit-exact operations. The project redraws the boundary between model and compute platform, with implications for self-hosted stacks and data s...
A detail in a pull request reignites the debate on a class of 120-billion-parameter LLMs. For teams managing self-hosted deployments, the size reshapes calculations around VRAM, quantization, and TCO, without official announcements. The signal points...
A pull request in the QwenLM/qwen-code repository has drawn attention to a possible 120-billion-parameter model. It is not an official announcement, but the 120B class touches a central issue for on-premise deployments: aggregated VRAM, quantization,...
