Alibaba Cloud Releases Qwen3.8-2.4T-A95B and Qwen3.8-Max: 2.4-Trillion Parameter Open MoE with Gated DeltaNet Linear Attention

Alibaba Cloud's Qwen team has shocked the global AI landscape by releasing the post-trained weights for **Qwen3.8-2.4T-A95B** alongside the cloud-managed **Qwen3.8-Max** service.

Gated DeltaNet: Sub-Quadratic Linear Attention At 2.4 trillion total parameters with 95 billion activated per token across 92 layers, Qwen3.8 introduces a hybrid layout: - 23 repeating blocks consisting of: `3 × (Gated DeltaNet → MoE) → 1 × (Gated Attention → MoE)`. - 128 linear attention heads for Values and 16 for Query-Key projections. - Sub-quadratic memory scaling across ultra-long prompts.

Controllable Reasoning: reasoning_effort & preserve_thinking Addressing the needs of complex coding agents, Qwen3.8 introduces deep reasoning control: - `reasoning_effort`: Allows developers to dynamically allocate thinking tokens between 0 (instant zero-shot generation) and 64,000 thinking tokens for formal verification. - `preserve_thinking`: Carries previous chains of thought across multi-turn developer sessions, avoiding token re-computation when debugging complex software repositories.