This paper presents the SEOBNR-PM waveform model, which combines post-Minkowskian (PM) and effective-one-body (EOB) approaches to simulate gravitational waveforms from binary black hole mergers. The model is built upon the successful SEOBNRv5 model, with key improvements in the EOB Hamiltonian derived from a PM expansion of the two-body scattering angle. The new model incorporates PM corrections to the EOB Hamiltonian, including both non-spinning and spinning terms, and is calibrated to numerical-relativity (NR) simulations. The model performs well, showing a lower median mismatch compared to SEOBNRv5 when tested against 441 NR simulations. It also shows better agreement with NR results for binding energy and spin contributions. The model is implemented in the pySEOBNR code, which allows for efficient development and calibration. The model is validated against NR simulations, showing good agreement in the inspiral, merger, and ringdown phases. The model is particularly effective for systems with high velocities or large eccentricities. The paper also discusses the importance of waveform accuracy for future gravitational wave detectors and the need for improved models to avoid false claims of General Relativity violations. The model is a significant step forward in combining PM and EOB methods for gravitational wave modeling.This paper presents the SEOBNR-PM waveform model, which combines post-Minkowskian (PM) and effective-one-body (EOB) approaches to simulate gravitational waveforms from binary black hole mergers. The model is built upon the successful SEOBNRv5 model, with key improvements in the EOB Hamiltonian derived from a PM expansion of the two-body scattering angle. The new model incorporates PM corrections to the EOB Hamiltonian, including both non-spinning and spinning terms, and is calibrated to numerical-relativity (NR) simulations. The model performs well, showing a lower median mismatch compared to SEOBNRv5 when tested against 441 NR simulations. It also shows better agreement with NR results for binding energy and spin contributions. The model is implemented in the pySEOBNR code, which allows for efficient development and calibration. The model is validated against NR simulations, showing good agreement in the inspiral, merger, and ringdown phases. The model is particularly effective for systems with high velocities or large eccentricities. The paper also discusses the importance of waveform accuracy for future gravitational wave detectors and the need for improved models to avoid false claims of General Relativity violations. The model is a significant step forward in combining PM and EOB methods for gravitational wave modeling.