
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.
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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.

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 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 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 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 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.

Alibaba unveils Qwen-branded AI smart glasses at MWC Barcelona with pre-orders starting March 2, challenging Meta's dominance in a wearable AI market that tripled last year.

Alibaba releases official FP8-quantized weights for the Qwen 3.5 flagship and 27B dense model, cutting memory requirements roughly in half and enabling deployment on 8x H100 GPUs with native vLLM and SGLang support.

Comparing Kimi K2.5 and Qwen3.5 Flash - Moonshot AI's trillion-parameter frontier model against Alibaba's cheapest and fastest API offering.

Comparing Kimi K2.5's 1T-parameter benchmark dominance against Qwen3.5-122B-A10B's extraordinary parameter efficiency - and why the smaller model is harder to dismiss than the numbers suggest.

Comparing Kimi K2.5's trillion-parameter benchmark dominance against Qwen3.5-27B's single-GPU accessibility - two models from entirely different tiers that both have compelling use cases.

A detailed comparison of Kimi K2.5 and Qwen3.5-35B-A3B - a 1T parameter frontier model with agent swarms versus a 35B model that runs on a single consumer GPU.