Qwen 3.6 Ships a 35B MoE That Codes Like Models 10x Its Size
Alibaba's Qwen 3.6-35B-A3B activates only 3B of its 35B parameters per token, scores 73.4% on SWE-bench Verified, handles video and images, and ships under Apache 2.0.
Articles Tagged "Alibaba"
Alibaba's HappyHorse Claims Video AI Crown - No Weights Yet
HappyHorse-1.0 topped the Artificial Analysis Video Arena with a 52-Elo gap over Seedance 2.0 - but the 'open source' model has no public weights, no inference code, and no API.
Qwen3.5-Omni Does 10-Hour Audio and 4M Video Frames
Alibaba's Qwen3.5-Omni handles audio, video, images, and text in a single model pass - and generates speech in real time. The Plus variant hits SOTA on 215 benchmarks and edges out Gemini 3.1 Pro on audio tasks.
Alibaba Qwen3.6-Plus Launches With 1M Context Window
Alibaba officially launches Qwen3.6-Plus, a 1-million-token context model built for enterprise agentic coding and multimodal reasoning, now free on OpenRouter.
Alibaba's C950 - First RISC-V CPU with Native LLM Inference
Alibaba's T-Head division launched the XuanTie C950, a 5nm 3.2GHz RISC-V server chip that sets a new world record for RISC-V single-core performance and natively runs billion-parameter models like DeepSeek V3 and Qwen3.
75% of AI Coding Agents Break Working Code Over Time
Alibaba's SWE-CI benchmark tested 18 AI models on 100 real codebases across 233 days of maintenance. Most agents accumulate technical debt and break previously working code. Only Claude Opus stays above 50% zero-regression.
Qwen's Tech Lead Junyang Lin Steps Down From Alibaba
Junyang Lin, the 32-year-old architect behind Alibaba's Qwen open-source AI models, announces his departure in a brief tweet - the fourth major exit from Tongyi Lab in two years.
Qwen 3.5 Small Series Ships Four Models From 0.8B to 9B
Alibaba completes the Qwen 3.5 lineup with four small models - 0.8B, 2B, 4B, and 9B - all natively multimodal, 262K context, Apache 2.0. The 9B outperforms last-gen Qwen3-30B and beats GPT-5-Nano on vision benchmarks.
Qwen3.5-0.8B
Qwen3.5-0.8B is the smallest natively multimodal model in the Qwen 3.5 family - 0.8B parameters handling text, images, and video with 262K context. MathVista 62.2, OCRBench 74.5. Apache 2.0.
Qwen3.5-2B
Qwen3.5-2B is a 2B dense multimodal model with 262K context, thinking mode, and native vision including video understanding. OCRBench 84.5, VideoMME 75.6. Apache 2.0 licensed.
Qwen3.5-4B
Qwen3.5-4B is a 4B dense multimodal model that matches Qwen3-30B on MMLU-Pro and beats GPT-5-Nano on vision benchmarks. Runs on 8GB VRAM, Apache 2.0 licensed, 262K-1M context.
Qwen3.5-9B
Qwen3.5-9B is a 9B dense model that outperforms Qwen3-30B on most benchmarks and beats GPT-5-Nano on vision tasks. Natively multimodal with 262K-1M context, Apache 2.0 licensed.
