… report, we develop Qwen2-Audio, with a primary focus on enhancing its instruction-following
capabilities. Qwen2… Compared to previous models, Qwen2-Audio significantly scales up the …

… In this report, we introduce the Qwen2.5-Coder series, a … , and balanced data mixing,
Qwen2.5-Coder demonstrates … We believe that the release of the Qwen2.5-Coder series will …

… Qwen2.5-Math models. Lastly, similar to the process used for the Qwen2-Math-Instruct models,
we construct the Qwen2.5-… of initializing from the Qwen2 series, we leverage the Qwen2.5 …

… (I2I) reconstruction, effectively aligning the latent representations between Qwen2.5-VL and
MMDiT. Furthermore, we separately feed the original image into Qwen2.5-VL and the VAE …

… (2) Model-based Reward with Reference Answer: In this approach, we provide a reference
answer for each query and prompt Qwen2.5-72B-Instruct to score the model’s response …

… In this initial phase, we leverage Qwen2.5-VL to identify and discard queries that are not
readily verifiable. Queries with ambiguous instructions are minimally revised to enhance clarity …

… In Qwen3-Omni, we retain the chunked-prefilling mechanism as implemented in Qwen2.5-Omni,
whose audio and vision encoders are capable of outputting chunks along the temporal …

… Omni, we retain the chunked-prefilling mechanism as implemented in Qwen3-Omni and
Qwen2.5-Omni, whose audio and vision encoders are capable of outputting chunks along the …

We present Qwen3-Coder-Next, an open-weight language model specialized for coding
agents. Qwen3-Coder-Next is an 80-billion-parameter model that activates only 3 billion …

… Auto Labeling To annotate the unlabeled data, we design tailored annotation instructions
and leverage multiple versions of Qwen models, such as Qwen2.5-72B-Instruct and Qwen3-…