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Ling-3.0-flash-Sante: 124B-parameter medical MoE model released on HuggingFace

On October 19, 2026, the inclusionAI/Ling-3.0-flash-Sante model for text-generation was published on HuggingFace. This is a specialized medical version of Ling-3.0-flash: the author claims 124B total parameters, of which 5.1B are activated per token, and a context of up to 256K tokens. Details are on the model page.

What it means

The model is licensed under MIT and published in safetensors. The full repository weighs 237.5 GB, with the largest file at 14.4 GB. For running on your own hardware there are two GGUF builds; the most compact working one is IQ4_XS by AtomicChat at 72.8 GB. This means that even in quantized form the model requires several GPUs or a system with a large amount of system RAM. The architecture is MoE, which explains the difference between the total parameter count and the number active per token. In the same days, Ling-3.0-tiny-UBTree was released in the lineup. For those following local models, related news is collected in the CPU3D news feed.
Ling-3.0-flash-Sante — medical MoE model HF HuggingFace model release October 19, 2026 MIT license 124B Parameters total count 5.1B active per token MoE Architecture mixture of experts gap between total and active 256K Context tokens window length Model storage safetensors format full repo 237.5 GB largest file 14.4 GB GGUF builds: IQ4_XS by AtomicChat — 72.8 GB
How the method works. The diagram was drawn based on this news note.

See also