This report synthesises findings from 10 peer-reviewed papers addressing the following research question: How does DeepSeek-V3's auxiliary-loss-free load balancing strategy impact token throughput and latency on long-context reasoning benchmarks compared to traditional MoE routing mechanisms. 10 claims were extracted from source literature; 9 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.2/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: How does DeepSeek-V3's auxiliary-loss-free load balancing strategy impact token throughput and latency on long-context reasoning benchmarks compared to traditional MoE routing mechanisms? Autonomous literature synthesis. Automated review score: 8.2/10. Full text and citation available at Assignee Research.