Experiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding

NVIDIA Developer published “Experiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding” dated 2026-08-26.

According to the NVIDIA Developer feed, alibaba released the model weights for Qwen3.8-Flash-Next as a preview of the upcoming Qwen4 architecture for developers to experiment with and evaluate.

The same item also notes that alibaba released the model weights for Qwen3.8-Flash-Next as a preview of the upcoming Qwen4 architecture for developers to experiment with and evaluate.

The same item also notes that it’s a multimodal mixture-of-experts (MoE) model with a 125B-parameter main model supplemented by an additional 51B N-gram embeddings, with 6B parameters activated per token.

According to the NVIDIA Developer feed, alibaba released the model weights for Qwen3.8-Flash-Next as a preview of the upcoming Qwen4 architecture for developers to experiment with and evaluate.

The same item also notes that it’s a multimodal mixture-of-experts (MoE) model with a 125B-parameter main model supplemented by an additional 51B N-gram embeddings, with 6B parameters activated per token.

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Open the original at https://developer.nvidia.com/blog/experiment-with-qwen3-8-flash-next-on-nvidia-gb300-nvl72-for-agentic-coding/ to read the publisher’s full post, quotes, and any figures they published.