Alibaba

An open robotic value-foundation-model family from Alibaba DAMO Academy and Hupan Lab. It learns temporal distance to a language-specified goal from m…

Alibaba's first open-weight Qwen-Max-class release and its largest public model: a 2.4T-parameter MoE with 95B active per token. Its 92-layer hybrid s…

Tongyi Lab's 14B end-to-end character-animation DiT consumes a driving video directly, avoiding lossy pose or motion extractors. A dual branch, time-a…

Names and measures Solution Hacking: frontier models reaching correct answers on science benchmarks through invalid shortcuts (numerical search, enume…

Trains VLMs to use visual tools as a compositional and adaptive capability rather than fixed-tool-space grounding: a hierarchical trajectory-synthesis…

Multimodal embedder (2B/4B/9B, Qwen3.5 backbones) emitting dense + SPLADE-style sparse embeddings in one causal pass — text, image, and video, i…

DAMO Academy's medical MLLM (8B/32B, Apache 2.0) on Qwen3-VL-32B with a DINOv2 + CLIP-ConvNeXt cascade-fusion vision stack, native 2D and 3D NIfTI CT/…

DAMO Academy and Hupan Lab's embodied foundation-model family adds native 3D grounding, contact-point prediction, and an action model spanning Unitree…

Tongyi/Wan's ~25B single-stage diffusion long-form music generator: five-minute multilingual songs with dual-stem (vocals + BGM) output; claims 7.43%…

A 14B image-to-video character-animation model from Alibaba's Wan (Tongyi Wanxiang) video team, specialized for dance and full-body character motion &…

DAMO Academy's embodied world models, released as a pair (both HF-trending at launch). RynnWorld-4D predicts future RGB, depth, and optical flow from…

A universal audio-generation framework that unifies speech, sound, and music in a single model by extending autoregressive next-token prediction from…

Qwen's first "native language world model" for agents: given an agent action, it predicts the next environment state across seven agent domains (MCP t…

Qwen's entry into robotics: three simultaneous technical reports, with weights explicitly not released. RobotNav is a navigation foundation model with…

Pathology vision foundation model from DAMO Academy (Alibaba Group), CAS Institute of Automation, and Hupan Lab. ViT-L backbone (plus a ViT-B "DaX-Bas…

Alibaba's new flagship reasoning model, unveiled at the 2026 Alibaba Cloud Summit on May 20 after debuting anonymously on LM Arena around May 14. Prop…

Shows that full-attention LLMs are already intrinsically sparse and can be converted into highly sparse models with only a few hundred training steps…

"Think When Needed: Adaptive Reasoning-Driven Multimodal Embeddings with a Dual-LoRA Architecture." Proposes a dual-LoRA setup that attaches a reasoni…

Qwen Team with MBZUAI (and KAUST): a systematic study of structured pruning and knowledge distillation for MoE models at pretraining scale. Findings:…

Open-weight Qwen3.6 family released under Apache 2.0. Two flagships: Qwen3.6-27B (dense, 27B, 64 layers, hybrid gated DeltaNet + gated attention) achi…

Top proprietary tier of the Qwen3.6 generation and the first fully closed-weights Qwen Max flagship — released only as a Preview ("smarter, shar…

Addresses when agentic multimodal models should use external tools versus relying on internal knowledge. Proposes HDPO (Hybrid Decoupled Policy Optimi…

Enterprise-focused frontier model with 1M token context (up to 65,536 output tokens). Always-on chain-of-thought reasoning and native function calling…

Introduces Think-Anywhere, enabling LLMs to invoke reasoning blocks at arbitrary token positions during code generation, rather than only before imple…

Addresses skill routing for LLM agents at scale (10K+ skills). Key finding: hiding the skill body causes a 31–44 percentage point drop in routin…

Fourth generation of the Qwen model family. Qwen3.5-397B-A17B native VLM built on Qwen3-Next architecture. 201 languages and dialects supported. 1M co…

Open web world model for training and evaluating browser agents: predicts next-page state given the current state and a candidate action. Three sizes…

Dataset for training reasoning reward models.

Qwen's open speech-recognition line (backfilled from January 2026; Transformers-native "-hf" ports shipped June 26): 0.6B and 1.7B models built on the…

Benchmark for evaluating complex agentic planning.

10-million-token benchmark for corpus-level analysis and reasoning — answers require global integration, comparison, and statistical aggregation acros…

Polymath learning asks how far reinforcement learning can go with a single, carefully engineered training problem. Starting from Qwen2.5-7B-Base, the…

A training-infrastructure system for multi-task agentic reinforcement learning on disaggregated hardware. Agentic RL workloads mix compute-bound prefi…

Safety-specialized guardrail model for real-time token stream moderation.

"Fin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models." A process reward model purpose-built for financ…

Image generation model family. Qwen-Image (20B MMDiT) excels at text rendering in Chinese and English. Qwen-Image-2.0 (7B) unifies generation and edit…

CLI tool for terminal-based agentic coding and codebase analysis.

Third-generation coding-specialized model family including Qwen3-Coder-480B and Qwen3-Coder-Next.

Awarded **Best Paper at NeurIPS 2025**, this research introduces a foundational architectural modification for transformers: applying a head-specific…

Third generation of the Qwen model family. Introduced a massive 36-trillion token pretraining dataset. Includes dense, MoE, multimodal, speech, and re…

High-quality mathematical reasoning dataset.

End-to-end multimodal model processing text, images, audio, and video with real-time speech generation. Thinker-Talker architecture. Over 80k download…

Reasoning model following the chain-of-thought (CoT) paradigm.

Vision-language model with dynamic resolution processing and absolute time encoding.

Multimodal reasoning model following the chain-of-thought (CoT) paradigm.

Benchmark for evaluating the step-by-step logic of LLMs.

The "18-trillion token" series. Released sizes: 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B, plus a proprietary MoE model (Qwen2.5-Max).

Naive Dynamic Resolution for variable-resolution visual processing. Available in 2B, 8B, and 72B variants.

Coding-specialized model family. Code-specific models (0.5B-32B) pre-trained on 5.5T tokens.

Math-specialized model family. Includes the Qwen2.5-Math series (1.5B, 7B, 72B) which introduced Tool-Integrated Reasoning (TIR).

Significantly improved multilingual capabilities. Sizes: 0.5B, 1.5B, 7B, 72B, and the 57B-A14B MoE.

Major update (the "Qwen2 Beta") introducing 0.5B, 1.8B, 4B, 7B, 14B, 32B, 72B, and 110B dense models, alongside a 14B MoE variant.

Audio model family. Evolution from Qwen-Audio (2023) to Qwen2-Audio-7B (Aug 2024).

Python framework for building agents with tool-calling, RAG, and code execution.

C++ implementation for efficient local inference of Qwen models.

First-generation vision-language model in the Qwen family.

First generation of the Qwen large language model series, spanning 1.8B to 72B parameters.

Contrastive vision-language pretraining specifically for Chinese. Predates the Qwen branding.

Unified sequence-to-sequence framework for multimodal tasks. Predates the Qwen branding.

Multi-modality-to-multi-modality mega-transformer, including the M6-10T (10 trillion parameters) and M6-T sparse models. Predates the Qwen branding.