Qwen AI models

Qwen-Image 3.0 Pro is the high-quality tier of the Qwen-Image 3.0 series, offering stronger text rendering, more realistic textures, and better semantic adherence for both text-to-image (T2I) and image-to-image/editing (I2I). Output resolution ranges from 512x512 up to 2048x2048 (PNG).

Qwen-Image 3.0 is a general-purpose image generation and editing model that balances quality and speed. It excels at complex text rendering (multi-line, paragraph-level layouts), fine detail, and realistic textures, and supports both text-to-image (T2I) and image-to-image/editing (I2I) on DashScope's multimodal-generation endpoint.

Qwen Image 2512 is an improved version of Qwen Image with better text rendering, finer natural textures, and more realistic human generation. This 20B MMDiT model achieved top ranking among open-source models after 10,000 blind comparison rounds on AI Arena, released December 31, 2025, and is licensed under Apache 2.0.

Qwen3.8-27B is Alibaba's compact, deployment-friendly open-weight model from the Qwen3.8 generation, released under Apache 2.0. It is a 27.8-billion-parameter dense model using a hybrid decoder that alternates Gated DeltaNet linear attention with grouped-query full attention, with native text, image, and video understanding, a 262,144-token context window, and configurable reasoning effort toggled on or off per request. It targets coding, professional work, research, and long-horizon agentic tasks in a footprint small enough to self-host on high-end consumer hardware.

Qwen3.8-Max is Alibaba's flagship sparse mixture-of-experts model, with 2.4 trillion total parameters and approximately 95 billion active per forward pass, accepting text, image, and video input and returning text with a 1M-token context window. Hybrid thinking mode is enabled by default with three reasoning-effort tiers, and pricing is flat across the full context window with no long-prompt surcharge. Target workloads include software engineering, long-horizon agentic work, office productivity, and visual tasks such as turning screenshots or design files into working pages.

Qwen-Image is an image generation foundation model in the Qwen series that achieves significant advances in complex text rendering and precise image editing. It supports parallel CFG and LoRA merging (up to 3 LoRAs), configurable inference steps, and an optional turbo mode for faster generation using optimized settings (10 steps, CFG=1.2).

Qwen3-Embedding-8B is the largest model in the Qwen3 Embedding series, purpose-built for text embedding and retrieval tasks. It ranks No.1 on the MTEB multilingual leaderboard, supports 100+ languages, and produces embeddings up to 4096 dimensions with support for user-defined output dimensions (Matryoshka Representation Learning) from 32 to 4096. The model is instruction-aware, allowing custom task instructions to be prepended to inputs for improved retrieval performance, and supports a 32K token context length.

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for tasks like math, coding, and logical inference, and a "non-thinking" mode for faster, general-purpose conversation. The model demonstrates strong performance in instruction-following, agent tool use, creative writing, and multilingual tasks across 100+ languages and dialects. It natively handles 32K token contexts and can extend to 131K tokens using YaRN-based scaling.