Released on Sep 19, 2024
Ultra-compact 0.5B-parameter model. Runs on any hardware, even embedded: ideal for lightweight summarization and low-power local devices.
Flagship Max da 2,4 trilioni di parametri con ~95B attivi, contesto da 1M token e primo modello Max aperto dei pesi, oltre al Qwen3.8-27B Apache 2.0.
Flagship Qwen3.5-397B-A17B basata su MoE sparsa con attenzione lineare (Gated DeltaNet), multimodalità nativa e 201 lingue.
Generazione successiva con modalità ibride di ragionamento (thinking e non-thinking), pretraining raddoppiato a ~36 trilioni di token e 8 taglie open-weight.
Rilasciata insieme alla famiglia Qwen2.5 con taglie da 0,5B a 72B, contesto fino a 128K token e licenza Apache 2.0.
Visit the official site to download, learn more and start using Qwen2.5 0.5B.
7B open-weight model (32-layer DiT) that unifies text-to-image generation up to 2048x2048, editing with up to 10 reference images, and native RGBA transparency. Designed to run locally on 16GB+ VRAM; supported by diffusers and ComfyUI.
Clear step up in reasoning and instruction quality over 8B models. Excellent for coding, agents and structured writing on 16GB GPUs or Macs with 32GB RAM.
Near-70B quality at a fraction of the size: the sweet spot for advanced use. Excellent in Italian, code and reasoning. Needs 24GB+ VRAM.
