Solar radiation modification (SRM) is proposed to temporarily offset global warming, yet its impact on temperature extremes at regional scales remains uncertain. This study examines how temperature extremes over Northern Africa respond to two SRM scenarios (G6solar and G6sulfur) relative to high- (SSP5-8.5) and intermediate-emission (SSP2-4.5) pathways, with emphasis on their evolution, relationship with mean temperature, and structural characteristics. We analyse eight temperature extreme indices (TXx, TXn, TNx, TNn, TX95p, TX5p, TN95p and TN5p) using simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6). Changes are evaluated for near-future (2020–2054) and far-future (2065–2099) periods, integrating spatial patterns, temporal evolution, distributional shifts, and extreme-mean relationships. Asymmetry diagnostics are further applied to assess differences between warm–cold and day–night responses. Results show that SRM suppresses the intensification of warm temperature extremes relative to SSP5-8.5. However, despite achieving similar mean temperature, SRM does not reproduce the behaviour of temperature extremes under SSP2-4.5. Frequency-based indices exhibit the strongest divergence, particularly in the far-future, with more frequent warm extremes and fewer cold events under SRM compared with the intermediate-emission pathway. The relationship between extreme and mean temperature is approximately linear but varies across scenarios, with differences in sensitivity and spread indicating forcing-dependent relationship. In addition, SRM modifies the structure of temperature extremes, with an asymmetric response of upper and lower tails and smaller differences between daytime and night-time extremes, leading to a redistribution of the temperature distribution rather than a uniform shift. These results suggest that reducing global mean temperature does not fully restore the behaviour of temperature extremes. Instead, SRM produces a distinct, scenario-dependent climate that differs from both high- and intermediate-emission pathways. This highlights the need to assess climate intervention strategies using metrics that capture both mean conditions and the distribution and structure of extremes.