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Qwen (Alibaba) Latest news

Follow open releases and updates across Alibaba’s Qwen family, from flagship models to small on-device models.

9 picksPast 30 days: 4 itemsTotal: 84 items

Latest pick Key moments ↓

Qwen (Alibaba) top picks

Sep 22

Sep 22TueItems 1–9
  1. Unsloth AIAI score70

    Qwen-Image-2.1 runs locally on 12GB VRAM using Unsloth GGUFs

    Unsloth says the 7B Qwen-Image-2.1 text-to-image and editing model can run locally on 12GB VRAM using its GGUF builds. It also states that the model performs on par with Nano Banana 2.0, and that Dynamic FP8 can run on 6GB of VRAM via offloading for higher quality. The image lists int8 at 7.26 GB with mean LPIPS 0.064 and fp8 at 7.12 GB with mean LPIPS 0.112, and says int8 is the default.

    AIWhy it matters: The post gives concrete local-run settings, VRAM figures, and GGUF and FP8 options, which helps readers judge whether the model fits their hardware.

Sep 20

Sep 20Sun
  1. Qwen · new models on Hugging FaceAI score62

    Qwen releases Qwen-Image-2.1 prompt rewriter for image editing on Hugging Face

    Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with 7B visual generation parameters. The Hugging Face page for Qwen-Image-2.1-PE-I2I is a fine-tuned Qwen3.5-VL 9B prompt rewriter that turns vague editing instructions and input images into precise editing prompts, supporting up to 10 reference images.

    AIWhy it matters: The model card documents usage with transformers and diffusers, letting readers see how the editing prompt rewriter connects to the generation pipeline.

  2. Qwen · new models on Hugging FaceAI score62

    Qwen releases open-source Qwen-Image-2.1 with a prompt rewriting model

    Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with a 7B-parameter visual generation component. The release also includes Qwen-Image-2.1-PE-T2I, a fine-tuned Qwen3.5-VL 9B model that rewrites brief image requests in any language into detailed English prompts with a recommended aspect ratio.

    AIWhy it matters: The release pairs a 7B visual generation component with a separate prompt rewriting model, showing how a brief image request becomes a detailed English prompt before rendering.

Sep 13

Sep 13Sun
  1. Qwen · new models on Hugging FaceAI score67

    Qwen releases open-source Qwen-Image-2.1 for generation and editing

    Qwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with 7B parameters in its visual generation component. The model can generate regular or transparent RGBA images, supports up to 10 reference images for editing, and is licensed under the Qwen Research License Agreement.

    AIWhy it matters: The source specifies the 7B visual component, transparent RGBA output, and up to 10 reference images, which helps readers judge its fit for generation and editing workflows.

Aug 27

Aug 27Thu
  1. Qwen · new models on Hugging FaceAI score62

    Qwen-Drive-1.0 releases open weights for driving VQA, perception, and planning

    Qwen has published Qwen-Drive-1.0-4B on Hugging Face, a vision-language model for autonomous driving built on Qwen3.5-4B. The release includes a BEV perception head and two Planning Experts, planner-sft and planner-rl, with code and an inference example in the linked GitHub repository.

    AIWhy it matters: The source gives concrete benchmark results and a runnable setup, letting readers judge how a driving VLM with planning and perception heads compares with existing systems.

Aug 26

Aug 26Wed
  1. Unsloth AIAI score78

    Unsloth explains how to run Qwen3.8-Flash-Next locally on 75GB RAM

    Unsloth announces that Qwen3.8-Flash-Next can be run locally through its GGUF quantizations. The source says the 1-bit version needs 75GB of RAM or unified memory, and that the 125B MoE model is reported to outperform Claude-Opus-4.6 (Max).

    AIWhy it matters: The source gives concrete local hardware requirements, quantization sizes, and a guide, showing how a 125B MoE model can run on a 75GB RAM setup.

Aug 24

Aug 24Mon
  1. Qwen · new models on Hugging FaceAI score75

    Qwen3.8-Flash-Next releases open weights for a hybrid-attention architecture

    Qwen released open weights for Qwen3.8-Flash-Next, a 125B-parameter model with 6B activated, built on a new hybrid architecture with Gated DeltaNet and Qwen Sparse Attention. The model has a native 262,144-token context length, extensible to 1,000,000 tokens, and the source reports benchmark results across coding, agent, and vision tasks.

    AIWhy it matters: The release pairs a new hybrid attention and gated residual architecture with open weights and benchmark results, giving architecture-focused readers a concrete case to compare against prior long-context designs.

Aug 7

Aug 7Fri
  1. Qwen · new models on Hugging FaceAI score88

    Qwen releases open-weight Qwen3.8-2.4T-A95B, a 2.4T-parameter MoE model

    Qwen has released the Qwen3.8-2.4T-A95B model weights on Hugging Face, with 2.4T total and 95B activated parameters in a mixture-of-experts design. The release supports reasoning_effort levels and a 262,144-token native context extensible to 1,010,000 tokens, and it is text-only with thinking mode always on. The source reports benchmark results against Opus 4.8, Fable 5, GPT 5.6 Sol, and Qwen3.7-Max, and says the official Qwen3.8-Max API adds vision input and a 1M default context.

    AIWhy it matters: The model card gives parameters, architecture, reasoning controls, and benchmark tables against named rival models, showing what an open release of this scale actually offers.

Aug 5

Aug 5Wed
  1. Qwen · new models on Hugging FaceAI score79

    Qwen3.8-27B releases dense vision-language model with thinking controls

    Alibaba's Qwen team has released Qwen3.8-27B on Hugging Face as a 27B dense model with native image and video understanding. The model card reports gains over Qwen3.6-27B on coding and agent benchmarks, including SWE-bench Pro at 61.7 versus 53.5. It adds reasoning_effort levels and preserve_thinking, and its hosted Qwen Cloud version is described as coming soon.

    AIWhy it matters: The model card gives per-benchmark comparisons with Qwen3.6-27B and named rivals, plus reasoning_effort and preserve_thinking controls for judging cost and agent behavior.

Key moments

Since 2023
  1. ModelUnsloth explains how to run Qwen3.8-Flash-Next locally on 75GB RAM
  2. ModelQwen3.8-Flash-Next releases open weights for a hybrid-attention architecture
  3. ModelQwen releases open-weight Qwen3.8-2.4T-A95B, a 2.4T-parameter MoE model
  4. ModelQwen3.8-27B releases dense vision-language model with thinking controls
  5. ModelQwen3.8 Max released
  1. ProductAlibaba announces Tongyi Qianwen
  2. ModelQwen-7B released as open weights
  3. ModelQwen1.5 released
  4. ModelQwen2 released
  5. ModelQwen2.5 and Qwen2.5-Coder released
  6. ModelQwQ-32B-Preview reasoning model released
  7. ModelQwen2.5-Max released
  8. ModelQwQ-32B released
  9. ModelQwen3 family released
  10. ModelQwen3-Coder released
  11. ModelQwen-Image released
  12. ModelQwen3-Max and Qwen3-Next released
  13. ModelQwen3.8 Max released
  14. ModelQwen3.8-27B releases dense vision-language model with thinking controls
  15. ModelQwen releases open-weight Qwen3.8-2.4T-A95B, a 2.4T-parameter MoE model
  16. ModelQwen3.8-Flash-Next releases open weights for a hybrid-attention architecture
  17. ModelUnsloth explains how to run Qwen3.8-Flash-Next locally on 75GB RAM