Speculative decoding techniques enable approximately threefold increases in token generation throughput on consumer-grade GPUs by predicting and verifying multiple tokens in parallel. This approach reduces latency and improves inference efficiency without requiring model retraining or specialized hardware. The results demonstrate practical scalability for large language model deployment on widely available graphics cards.