Continued advances in high-fidelity CFD algorithms, combined with increasing GPU performance, have led to the formulation of a new "CFD-4One" rule for the design of next-generation solvers: the ability to run simulations with one billion cells, over one million time steps, using one GPU (node), under one day. This target requires more than raw hardware performance as it demands a unified computational strategy that couples GPU-friendly, high-fidelity numerical schemes with geometry-agnostic mesh generation that efficiently run on modest hardware [1]. To meet these requirements, we introduce a GPU-accelerated framework built on an Octree mesh structure with fully integrated adaptive mesh refinement (AMR). The core design is intentionally methodagnostic: any numerical scheme that can operate on a hierarchical tree layout can be embedded within the framework. Here, we focus on results obtained with lattice Boltzmann methods, as they allow accurate prediction of unsteady turbulence on relatively coarse grids thanks to their excellent spectral properties. When combined with an optimized GPU implementation, the framework achieves performance equivalent to thousands of CPU cores on modern GPUs. This enables overnight billion-cell simulations on a single GPU (node), hence eliminating the need for large HPC clusters commonly required for scale-resolving aerodynamic analysis [2]. The framework is validated on industry-relevant benchmarks: LAGOON1 landing-gear, DrivAer car, and DARPA Suboff submarine. The results show accurate resolution of complex, unsteady 3D turbulent flows while fully satisfying the "CFD 4-One" rule. In the end, we show how the combination of simple ideas can help democratizing high-fidelity CFD, for users ranging from students to large industrial teams, by reducing computational and workflow barriers. [1] Coreixas C., "From Black-Box User to GPU & Octree CFD Developer: Lessons Learned from a 10-Year Journey", in 34th International Conference on Discrete Simulation of Fluid Dynamics (DSFD), 2025. [2] Coreixas C. and Latt J., "Democratizing Scale-Resolving Aerodynamics with GPU-based CFD on Adaptive Octrees", 3AF AERO Conference, 2026.