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HexStellar

HexStellar (HXS) is a native GPU-inference runtime that dramatically cuts the energy, heat, and hardware cost of serving large language models without changing model weights or outputs. Across five independent labs' flagship models on a single NVIDIA H100 it measured 17.2-27.4% less energy per card, up to 15C cooler silicon, and +167% more serving capacity at identical latency, with 100% identical results. It targets high-volume inference clusters first, then on-device and silicon integrations. HexStellar matters now because inference electricity and GPU supply are the dominant cost line for AI products; a drop-in layer that triples throughput on existing hardware is a rare, immediately valuable efficiency win. It is in early access with a small partner group, with signed, independently timestamped benchmark files.

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