Alibaba released the open weights for Qwen3.8-2.4T-A95B (Qwen3.8-Max), its largest open-weight model, bringing near-frontier capabilities to the open ecosystem. It has 2.4T total parameters with 95B activated per token. It’s a fine-grained mixture of experts (MoE) architecture with a hybrid of full and linear attention, a context window of up to one million tokens, and an output length of up to 128K, designed for demanding reasoning and agentic workloads.

Deploying a 2.4T parameter open-weight model requires data-center-scale accelerated compute. Inference at this scale depends on extreme co-design across chips, system architecture, and software. NVIDIA is working with the open-source ecosystem to bring the model to multinode deployments through optimized kernels, inference runtimes, and distributed serving recipes.

Without additional model tuning, the model achieves a throughput of over 4K tokens per second per GPU and over 350 tokens per second per user on NVIDIA GB300 NVL72 in FP8 precision on Day 0.…