Qwen (Qwen/Qwen2/Qwen2.5)

Editorial record

Plain-language summary

Qwen2.5 scales up the pretraining data to roughly 18 trillion tokens and refines the post-training pipeline (supervised fine-tuning plus reinforcement learning from preferences) across a range of model sizes from small to large. It targets improvements in instruction following, structured output, mathematics, and coding, and supports long context windows and many languages. The base and instruction-tuned weights are downloadable, giving practitioners a broad menu of sizes to fit different hardware budgets; most sizes are released under a permissive license while some larger ones use a more restrictive one, so it is open-weight.