Qwen

Alibaba Releases Open-Weight Qwen3.8-Flash-Next with 6B Active Parameters and Qwen 4 Architecture Preview

Alibaba has released the open weights for Qwen3.8-Flash-Next, a 125B-parameter multimodal Mixture-of-Experts (MoE) model that acts as an early architectural preview for the upcoming Qwen4 family. Operating with only 6B active parameters per token alongside a 51B N-gram embedding layer, the model targets cost efficiency across long-context reasoning, agentic coding, and multimodal workloads. Weights are publicly available on Hugging Face and ModelScope, while a managed production endpoint named

Thomson Reuters Deploys In-House Legal LLM 'Thomson' on Qwen Foundation to Cut API Dependency

Thomson Reuters has unveiled "Thomson," its first proprietary domain-specific language model built specifically for legal workflows. Developed over two years at an investment of roughly $40 million in engineering and compute infrastructure, the model is designed to perform specialized legal analysis without ongoing dependence on third-party frontier API providers like OpenAI or Anthropic. The model is built on top of Alibaba's open-weight Qwen architecture, utilizing Qwen3.5-397B as its foundat

Alibaba Plans Record 0.2B Hong Kong Share Offering to Fund Full-Stack AI Infrastructure and Models

Alibaba Group Holding announced a proposed equity placement in Hong Kong to raise HK$80 billion ($10.2 billion), allocating 100% of net proceeds to expand its full-stack artificial intelligence capabilities across custom silicon, cloud compute infrastructure, and foundation model development. Transaction Structure and Market Scale According to terms reviewed by Reuters, Alibaba is offering 710 million ordinary shares at HK$112.70 per share, representing a 3.6% discount to its latest closing p

Hugging Face Summer 2026 Report: Qwen Derivatives Top 150K as AI Agents Become Hub's Top Users

Hugging Face has published its State of Open Models: Summer 2026 report, detailing seven months of platform metrics that highlight a widening divergence between benchmark attention and production deployment. According to the analysis covering January through August 2026, public model repositories on the Hub grew from 2.43 million to 2.96 million, public datasets surpassed 1 million for the first time, and Spaces expanded to 1.44 million. Despite the catalog expansion, usage remains heavily conc

Unsloth Releases Dynamic V3.0 GGUFs for Qwen 3.8 27B with 1-Bit Mode and MTP

Unsloth AI has published its Dynamic V3.0 quantization suite for Alibaba's Qwen 3.8 27B model family, releasing optimized GGUF and NVFP4 checkpoints alongside public calibration matrices. The release claims a greater than 10 percent increase in top-1 percent accuracy at identical file sizes compared to standard baseline quantizations, while introducing an ultra-low-bit dynamic tier that operates within 8GB of memory. Qwen 3.8 27B is a dense vision-language model utilizing hybrid attention layer

Alibaba Demonstrates Native Qwen 3.8 27B Inference on XuanTie C950 RISC-V CPU at 30 Tokens per Second

Alibaba's semiconductor division, T-Head, announced day-zero native inference support for its latest open-weight model, Qwen 3.8 27B, running directly on the XuanTie C950 RISC-V server processor. Operating without discrete graphics processing units, the 64-core RISC-V chip delivered sustained decode throughput of 30 tokens per second alongside a time-to-first-token latency of 1.9 seconds. The benchmark demonstrates how architectural extensions on general-purpose open instruction sets can handle

Alibaba Releases Qwen 3.8 27B with Native Vision and Dynamic Reasoning Controls

Alibaba's Qwen research team has released Qwen 3.8 27B, an open-weight multimodal foundation model released under the Apache 2.0 license. The model combines 27 billion parameters with native vision processing, a 262,144-token maximum context window, and configurable inference-time reasoning controls. Under standard 4-bit quantization (Q4_K_M), the model compresses to approximately 17GB on disk, allowing local execution on consumer hardware with 24GB of VRAM or Apple Silicon unified memory syste

Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things

Alibaba's Qwen research lab released Qwen 3.8 27B, a 27-billion-parameter Apache 2.0 licensed AI model available in 17GB GGUF format that can run on high-end consumer laptops. The model supports vision, long contexts, and tool calling. The over-thinking problem Qwen's documentation describes the model as defaulting to xhigh for reasoning effort—a setting designed for complex tasks demanding thorough analysis. In practice, this causes the model to use its full 262,144 token context on even mun

Alibaba's Qwen becomes the world's most-downloaded open AI model family