Real-time conversational deliberation is a critical groupwise method for reaching decisions, solving problems, evaluating priorities, generating ideas, and producing insights. Unfortunately, real-time conversations are difficult to scale, losing effectiveness as groups grow above 5 to 7 members. Conversational Swarm Intelligence (CSI) is a new technology modeled on the dynamics of biological swarms. It aims to enable networked groups of any size to hold productive real-time deliberations that converge on unified solutions. CSI leverages the power of Large Language Models (LLMs) in a unique and powerful way, allowing real-time dialog among small local groups while simultaneously enabling efficient content propagation across much larger populations. In this way, CSI combines the benefits of small-scale deliberative reasoning and large-scale collective intelligence. In this study, we compare deliberative groups of 48 people using standard online chat to the same sized groups using a prototype chat-based CSI system called Thinkscape. Results show that participants using CSI contributed 51% more content (p<0.001) than those using standard chat, and the deliberations using CSI showed 37% less difference in contribution quantity between the most active vs least active members, indicating more balanced dialog. And finally, a large majority of participants preferred deliberating using the CSI system over standard chat (p<0.05) and re-ported feeling more impactful when doing so (p<0.01). These results suggest that Conversational Swarm Intelligence is a promising technology for enabling large-scale deliberation.