Leaked repository entries and official statements point to Qwen 4 models with up to 1M token context and a possible 120B class, while Qwen confirms 4.0 and 5.0 will remain open source. This reshapes self-hosted LLM planning around VRAM, quantization, and API-free deployment.
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 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,...
The pull request in qwen-code signals that Qwen4 targets a one-million-token window. For self-hosted inference the cost is not theoretical: the key-value cache grows with tokens and fills VRAM along with weights. Qwen4-27B makes multi-GPU setups or a...
Alibaba brings Qwen4 to a one-million-token context window. The news emerges from a pull request in qwen-code: Qwen4-27B is expected tomorrow at the Apsara event in the Netherlands, while Qwen4-max is dated November 1st with October 1st as a likely p...
