ALIBABA

Qwen3.8-27B is a 27B dense Apache-2.0 model that scores 61.7 on SWE-bench Pro and 42.2 on DeepSWE 1.1 - ahead of Opus 4.6 Max on both - while running on consumer hardware. Benchmarks, hardware math, and an honest when-to-use-it guide.

Alibaba released Qwen 3.8 Max on August 3, 2026 - a 2.4T-parameter MoE with 95B active per token, a 1M context window, and $2/$6 per million tokens on QwenCloud. It leads PaperBench at 93.0, and the weights open next week.

Alibaba shipped Qwen 3.7 Max on May 19, 2026 with a 1M token context window, Anthropic-compatible API, and agent-first architecture. Here is what developers need to know about pricing, performance, and when to use it.

Alibaba's flagship open-weight coding model. 480B total parameters, 35B active (MoE). Native 256K context, scales to 1M. Apache 2.0 license. State-of-the-art agentic coding.

Qwen3.6-27B keeps pulling developers back because it sits in the awkward, useful middle: strong enough for real local coding tasks, small enough for serious workstation testing, and cheap enough to benchmark honestly.

Alibaba's Qwen team has released Qwen 3 Coder, a 480-billion-parameter mixture-of-experts model that sets a new bar for open-source coding assistants. With 35 billion active parameters and support ...

Alibaba released Qwen 3 with eight models under an Apache 2 license, including a 235B mixture-of-experts flagship that beats Llama 4 Maverick on nearly every benchmark while being smaller and cheaper to run.