Large-scale distributed wireless networks that offer connectivity through multi-hop communication are considered for infrastructure-free, cost-effective connectivity in applications ranging from smart cities to disaster recovery. The practical capabilities of such networks (capacity, rate, delay, power consumption, etc.) are investigated in this work through numerical analysis of the cross-layer capacity problem. To keep analytical complexity manageable for massive multi-hop communication with millions of nodes (mega-scale), a symmetric hexagonal arrangement is adopted and the problem is decomposed into two coupled components: expected hop count and effective single-hop transmission capacity. This provides an upper-bound baseline, while real-world randomness may moderately degrade the results without changing their indicative order of magnitude. Using network symmetry and geometric partitioning, the discrete hop-count problem is converted into a continuous formulation, and a closed-form integral upper bound is derived via convex analysis. Results show that typical communication paths are two orders of magnitude shorter than the network diameter under realistic power-law interaction patterns, yielding better throughput and more favorable power consumption. To characterize transmission capacity, a cross-layer wireless model with full spatial reuse is developed, and a closed-form upper bound on aggregate interference is derived, allowing optimization of resource sharing to maximize per-node throughput. A clear picture of the network's capabilities is obtained by combining both components, showing how revised hop-count estimation and potential for aggressive resource reuse can overturn pessimistic assessments of such networks. It is demonstrated that these networks can potentially provide gigabytes of daily traffic per user, tens of Mbps for real-time services, sub-hundred-millisecond delay, and feasible power consumption sustained even with increased device density and population. Finally, future research directions toward scalable solutions are outlined: redesigning decision-making and protocol mechanisms for mega-scale networks; and enhancing devices to reduce power consumption and processing time for massive multi-hop communication, so the true physical limits of such networks can be enabled.