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Alibaba releases Qwen3.8-2.4T-A95B open-weight model for complex AI tasks

By PulseAugur Editorial · [2 sources] ·

Alibaba's Qwen team has released Qwen3.8-2.4T-A95B, the first open-weight model in their Qwen-Max class. This large model, featuring a hybrid attention architecture and 2.4 trillion parameters with 95 billion activated per token, is designed for demanding agentic and reasoning tasks. The release details how to deploy this model on Amazon SageMaker HyperPod using vLLM, enabling efficient inference with features like tool calling and speculative decoding. AI

IMPACT Sets a new benchmark for open-weight models, potentially accelerating enterprise adoption for complex agentic workloads.

RANK_REASON Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Alibaba releases Qwen3.8-2.4T-A95B open-weight model for complex AI tasks

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Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]
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2 independent sources
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model release, infra
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COVERAGE [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Dmitry Soldatkin ·

    Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM

    Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLLM. This walkthrough covers cluster provisioning, NVFP4 quantization, and an OpenAI-compatible endpoint with built-in reasoning, tool calling, and native MTP spe…

  2. Mastodon — mastodon.social TIER_1 English(EN) · aitools2u ·

    🤖 【AWS ML Blog】Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight mo

    🤖 【AWS ML Blog】Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLL... # AI # TechNews 🔗 https:// aws.amazon.com/blogs/machine-l earning/deployin…

    LINKS aws.amazon.com/…/deploying-qwen3-8-2-4t-a…

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