We analyze the public DESI full-shape clustering data using simulation-based priors (SBPs). Our priors are obtained by fitting normalizing flows to the distribution of effective field theory parameters measured from field-level simulations, themselves generated using tailored halo occupation distribution (HOD) models for each tracer. Incorporating SBPs in a power spectrum analysis significantly enhances $\mathrm{\Lambda }\mathrm{CDM}$ cosmological parameter constraints; in combination with baryon acoustic oscillations information from DESI DR2 and a Big Bang nucleosynthesis prior on the baryon density, we find the matter density parameter ${\mathrm{\Omega }}_m=0.2987\pm 0.0066$, the Hubble constant $H_0=68.80\pm 0.35\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$, and the mass fluctuation amplitude ${\sigma }_8=0.766\pm 0.015$ (or the lensing parameter $S_8=0.764\pm 0.018$), which are 1%, 40%, and 50% stronger than the baseline results, though with a notable downward shift in ${\sigma }_8$, driven by the quasar HOD assumptions. The SBPs also have a significant impact in extended models, with the dark energy figure-of-merit improving by 70% (20%) in a $w_0{w}_a\mathrm{CDM}$ analysis when combining with the CMB (and supernovae). In the SBP analysis, we do not find statistically significant evidence for dynamical dark energy: the equation of state parameters are consistent with a cosmological constant within $2.2\sigma$ ($1.4\sigma$) in analyses without (with) supernovae. The neutrino mass constraints are also enhanced, with the 95% limits $M_{\nu }<0.073\mathrm{eV}$ and $M_{\nu }<0.090\mathrm{eV}$ in $\mathrm{\Lambda }\mathrm{CDM}$ and $w_0{w}_a\mathrm{CDM}$, respectively. The latter is the strongest constraint obtained to date and reinforces the preference for the normal neutrino mass hierarchy, regardless of the background dynamics. While our results are sensitive to HOD modeling assumptions, they clearly demonstrate that the inclusion of small-scale information can significantly sharpen cosmological parameter constraints.

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• Cosmological parameters
• Dark energy
• Large scale structure of the Universe
• Data analysis