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Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72

12 August 2026 at 18:23
Decorative object.Alibaba released the open weights forΒ Qwen3.8-2.4T-A95B (Qwen3.8-Max), its largest open-weight model, bringing near-frontier capabilities to the open...Decorative object.

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…

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How to Choose Full-Stack Observability for NVIDIA AI Factories

12 August 2026 at 16:13
A worker in an AI factory.AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications. When performance degrades, identifying the...A worker in an AI factory.

AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications. When performance degrades, identifying the source can be difficult because a symptom observed at one layer may originate elsewhere in the stack. A full-stack observability strategy connects telemetry across these layers, helping infrastructure and operations teams detect problems…

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