Alibaba released Qwen3.8-2.4T-A95B-FP8, an open-weight, FP8-quantized MoE checkpoint with 2.4T total and 95B activated parameters, serving as the foundation for the hosted Qwen3.8-Max API. The model extends context to 1M tokens and shows significant benchmark gains over Qwen3.7-Max on coding and agentic tasks, according to Alibaba.
Alibaba released Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter MoE model with 95B active parameters, built on the Qwen3.5 architecture with hybrid Gated DeltaNet and Gated Attention layers. It introduces reasoning_effort and preserve_thinking controls and claims Qwen-Max-class performance in an open-weight release for the first time.
Alibaba's Qwen team has released Qwen3.8-2.4T-A95B-FP8, an open-weight, FP8-quantized MoE model with 2.4 trillion total parameters and 95 billion activated per token. It natively supports 262,144 tokens of context, extensible to 1,010,000, and forms the base for the hosted Qwen3.8-Max API.
Alibaba's Qwen team has released Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter mixture-of-experts model activating 95B parameters per token. The company claims it is the first open-weight release to reach Qwen-Max-class performance, with a hosted variant, Qwen3.8-Max, offering 1M-token context and vision input.