High Mountain Asia (HMA) hosts the largest mass of terrestrial ice outside the polar regions, where combined glacier and snow melting with high precipitation rates supplies water to hundreds of millions of people. HMA hydroclimate is controlled by complex topography that shapes the contrasting atmospheric circulation patterns of the monsoon influence in the South and the westerly fluxes on the West, making particularly challenging the understanding of climate variability in this area. Despite its importance, large observational gaps persist, particularly at high elevation, while the coarse resolution of global climate products and the limited spatial or temporal coverage of existing high-resolution simulations hinder robust analyses of long-term climate variability and trends. Here, we present high-resolution (7 km) simulations performed with the regional climate model MARv3.14 over two climatically contrasted regions of HMA: the westerly-dominated Pamir and the monsoon-dominated Central Himalaya. Covering the 1950–2025 period, these experiments constitute, to our knowledge, one of the longest continuous high-resolution regional climate simulations available over these regions. Model skill is evaluated using multiple gridded observational and reanalysis datasets, satellite-derived snow products, and extensive in situ observations, with a particular focus on temperature, precipitation, snow cover, and strong precipitation events. MAR successfully reproduces the main hydroclimatic characteristics of both regions despite their contrasting climatic influences. It captures the seasonal evolution of temperature, ranging from nearly 30 °C in the lowlands to below −20 °C at the highest elevations, the winter–spring precipitation maximum in the Pamir (up to ~110 mm ⋅ month⁻¹), the summer monsoon peak in the Central Himalaya (up to ~550 mm ⋅ month⁻¹), and the seasonal migration of the snowline from ~3800 to ~4800 m in the Pamir and from ~4700 to ~5400 m in the Central Himalaya. The evaluation reveals an elevation-dependent precipitation bias, characterized by underestimated precipitation at low elevations (<40–60 mm ⋅ month⁻¹), and excessive snowfall accumulation at high elevations, which is associated with cold temperature bias (<2–4 °C) and an excessive snow persistence. High-resolution dynamical downscaling substantially improves the representation of orographic precipitation and its spatial distribution over the Khumbu area compared to the driving ERA5 reanalysis. These simulations provide a new long-term climatic reference for the Pamir and Central Himalaya and a validated modelling framework for investigating climate variability, cryosphere evolution, and natural hazards, as well as high-resolution atmospheric forcing for impact models such as glacier mass balance, snowpack, and hydrological models. The validated model configuration also provides a robust and transferable framework for extending the simulations to the entire High Mountain Asia domain.