Tag: alibaba

  • Qwen-Image-3.0: 4.5k-Token Prompts, No Benchmarks, No Weights

    Qwen-Image-3.0: 4.5k-Token Prompts, No Benchmarks, No Weights

    Alibaba’s Qwen team launched Qwen-Image-3.0 on July 21, 2026 — the third generation of its image-generation model, built around a single claim: that generated images can now be useful, not just good-looking. The headline capability is a jump to 4.5k-token prompts, roughly 4.5× the instruction length its predecessors accepted, which the team says lets the […]

  • Qwen3.8-Max Preview: Alibaba’s 2.4T-Parameter Bid for the Frontier

    Qwen3.8-Max Preview: Alibaba’s 2.4T-Parameter Bid for the Frontier

    Alibaba’s Qwen team announced Qwen3.8-Max-Preview on July 19, 2026 — a 2.4 trillion-parameter multimodal model the team calls its most capable system yet, claiming performance “second only to Fable 5” among the models it evaluated. The preview landed just two days after Moonshot AI’s 2.8 trillion-parameter Kimi K3 open-weight release, underscoring how quickly China’s frontier […]

  • Qwen Releases FlashQLA: 2-3x Faster Linear Attention Kernels on Hopper

    Qwen Releases FlashQLA: 2-3x Faster Linear Attention Kernels on Hopper

    Qwen has open-sourced FlashQLA, a high-performance linear attention kernel library built on TileLang that targets the GDN (Gated Delta Network) Chunked Prefill workload. Released in late April 2026 under the MIT License, FlashQLA reports a 2–3× forward-pass speedup and roughly 2× backward-pass speedup over the FLA Triton kernels, and roughly 2× over FlashInfer 0.6.9 on […]

  • Luce DFlash Brings 2x Speculative Decoding to Qwen3.6-27B on a Single RTX 3090

    Luce DFlash Brings 2x Speculative Decoding to Qwen3.6-27B on a Single RTX 3090

    Luce DFlash now runs Qwen3.6-27B on a single RTX 3090, delivering up to 2× throughput over autoregressive decoding. The Lucebox Hub project, which hand-tunes LLM inference for specific consumer GPUs, ported its DFlash speculative decoding stack to Qwen3.6-27B in late April 2026. Because Qwen3.6-27B reuses the Qwen3.5 architecture string with identical layer and head dimensions, […]

  • Qwen3.6-27B: A Dense 27B Model That Beats a 397B MoE on Coding

    Qwen3.6-27B: A Dense 27B Model That Beats a 397B MoE on Coding

    On April 22, 2026, Alibaba’s Qwen team released Qwen3.6-27B — the first dense open-weight model in the Qwen3.6 generation. Released under Apache 2.0 on Hugging Face, the 27-billion-parameter multimodal model posts flagship-level agentic coding scores that beat the team’s previous-generation 397B Mixture-of-Experts flagship across multiple benchmarks, while fitting into a 16.8 GB Q4_K_M quantization that runs […]

  • Qwen3.6-35B-A3B: Alibaba Open-Sources a Frontier-Class Agentic Coder

    Qwen3.6-35B-A3B: Alibaba Open-Sources a Frontier-Class Agentic Coder

    On April 2, 2026, Alibaba’s Qwen team open-sourced Qwen3.6-35B-A3B — the first open-weight variant of the Qwen3.6 generation. Released under Apache 2.0 on Hugging Face alongside the proprietary Qwen3.6-Plus API model, the 35-billion-parameter Mixture-of-Experts model activates just 3B parameters per token while posting frontier-level scores on agentic coding and reasoning benchmarks, including 73.4 on SWE-bench […]

  • CoPaw-Flash-9B: Alibaba’s Agentic Fine-Tune of Qwen3.5-9B

    CoPaw-Flash-9B: Alibaba’s Agentic Fine-Tune of Qwen3.5-9B

    On March 30, 2026, Alibaba’s AgentScope team formally released CoPaw v1.0.0 — a personal AI agent workstation built around CoPaw-Flash-9B, an agentic fine-tune of Qwen3.5-9B. The model and the broader CoPaw framework are fully open-sourced under the AgentScope organization on Hugging Face and GitHub, positioning CoPaw as a lightweight, locally-runnable alternative to cloud-only AI agent […]

  • Qwen3.5-Omni: Alibaba’s Omnimodal AI Speaks 36 Languages and Codes from Voice

    Qwen3.5-Omni: Alibaba’s Omnimodal AI Speaks 36 Languages and Codes from Voice

    On March 30, 2026, Alibaba’s Qwen team released Qwen3.5-Omni — a natively omnimodal AI model that processes text, images, audio, and video while generating real-time speech output. Available in three sizes (Plus, Flash, and Light), the model claims 215 state-of-the-art benchmark results and introduces features like semantic interruption, voice cloning, and an emergent “Audio-Visual Vibe […]

  • Junyang Lin Steps Down as Qwen Tech Lead in Abrupt Departure

    Key points On March 3, 2026, Junyang Lin, the tech lead and public face of Alibaba’s Qwen open-source AI project, announced his departure in a brief post on X reading “me stepping down. bye my beloved qwen.” The exit came just 24 hours after the Qwen team shipped the Qwen 3.5 small model series, and […]

  • Qwen 3.5 Small Models: 9B Parameters That Beat 120B

    Qwen 3.5 Small Models: 9B Parameters That Beat 120B

    Key points On March 2, 2026, Alibaba’s Qwen team completed the Qwen 3.5 family with four small dense models of 0.8B, 2B, 4B, and 9B parameters for on-device and edge deployment. All four models are open-weight under Apache 2.0 and available on Hugging Face and ModelScope. Qwen3.5-9B outperforms models 3-13 times its size across language, […]