This study evaluates long-read and short-read sequencing for mitochondrial DNA (mtDNA) heteroplasmy detection. 592,315 bootstrapped datasets generated from two single-nucleotide mismatched ultra-deep sequenced mtDNA samples were used to assess basecalling error and accuracy, limit of heteroplasmy detection, and heteroplasmy detection across various coverage depths. Results showed high Phred scores of data with GC-rich sequence bias for long reads. Limit of detection of 12% heteroplasmy was identified, showing strong correlation (R ≥ 0.955) with expected heteroplasmy but underreporting tendency of high-level variants. Nanopore sequencing shows potential for direct applicability in mitochondrial diseases diagnostics, but stringent validation processes to ensure diagnostic result quality are required.