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We use the emulation framework CosmoPower to construct and publicly releaseneural network emulators of cosmological observables, including the CosmicMicrowave Background (CMB) temperature and polarization power spectra, matterpower spectrum, distance-redshift relation, baryon acoustic oscillation (BAO)and redshift-space distortion (RSD) observables, and derived parameters. Wetrain our emulators on Einstein-Boltzmann calculations obtained withhigh-precision numerical convergence settings, for a wide range of cosmologicalmodels including $\Lambda$CDM, $w$CDM, $\Lambda$CDM+$N_\mathrm{eff}$, and$\Lambda$CDM+$\Sigma m_\nu$. Our CMB emulators are accurate to better than 0.5%out to $\ell=10^4$ which is sufficient for Stage-IV data analysis, and our$P(k)$ emulators reach the same accuracy level out to $k=50 \,\,\mathrm{Mpc}^{-1}$, which is sufficient for Stage-III data analysis. We releasethe emulators via an online repository CosmoPower Organisation, which will becontinually updated with additional extended cosmological models. Our emulatorsaccelerate cosmological data analysis by orders of magnitude, enablingcosmological parameter extraction analyses, using current survey data, to beperformed on a laptop. We validate our emulators by comparing them to CLASS andCAMB and by reproducing cosmological parameter constraints derived from PlanckTT, TE, EE, and CMB lensing data, as well as from the Atacama CosmologyTelescope Data Release 4 CMB data, Dark Energy Survey Year-1 galaxy lensing andclustering data, and Baryon Oscillation Spectroscopic Survey Data Release 12BAO and RSD data.

High-accuracy emulators for observables in $\Lambda$CDM, $N_\mathrm{eff}$, $\Sigma m_\nu$, and $w$ cosmologies