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vLLM Semantic Router released Decision 3.0, five Apache-2.0 multimodal models from 0.8B to 27B.
vLLM Semantic Router released Decision 3.0, a family of five open multimodal decision models licensed under Apache-2.0. Sizes span 0.8B to 27B parameters. The models answer choice, yes/no, and score questions about text and images in a single call, without generating free-form text.
Analysis argues LLM inference cost per task is falling by orders of magnitude yearly through GPU, model, and inference-engine efficiency gains.
The post surveys evidence that AI cost per task is dropping by orders of magnitude annually: GPU power efficiency roughly doubles every two years, per-task costs fell about two orders of magnitude between 2025 and 2026 frontier charts, and inference engines like vLLM improved roughly 40% in energy efficiency over 15 months. Mixture-of-Experts architectures and serving-stack advances compound these gains. The author predicts LLMs become pervasive infrastructure within one to two years and run at frontier quality locally on commodity hardware within 3-6 years.