Background/Aim. Exosomal miRNAs are promising tumor biomarkers. This research explored the diagnostic value of serum exosomal miRNAs by analyzing the exosomal miRNAs derived from the serum of gastric cancer patients. Methods. Deep sequencing of exosomal miRNAs was performed using an Illumina HiSeq2500 sequencer on serum samples from three healthy subjects in the normal control group (group N) and six gastric cancer patients in the gastric cancer treatment group (group T). Bioinformatics analysis was performed on exosomal miRNA profiles to screen differentially expressed miRNA. In addition, target gene prediction, GO, and KEGG pathway enrichment analyses were performed. Finally, the serum exocrine bodies of 24 patients with gastric cancer and 24 normal controls were verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to confirm the findings. The receiver operating characteristic (ROC) curve of the subjects was plotted, and the area under the curve (AUC) was calculated with a 95% confidence interval (CI). Results. The exosomes were successfully extracted from the serum of gastric cancer patients, which showed a form of goblet vesicles or irregular circles, with an average particle size of approximately 102.3 nm. The exosomal marker proteins, CD9, CD63, TSG101, and calnexin, were positively expressed. Small RNA sequencing detected 15 different types of RNA components in the serum exosomes, and the most abundant one was miRNA. In the screened cohort, the downregulation of seven existing miRNAs and the upregulation of one existing miRNA were observed. Four of them were selected for confirmation, revealing that the expression of miR-10401-3p, miR-1255b-5p, and miR-6736-5p declined significantly in group T ( P < 0.05 ). In addition, the ROC curve showed that the AUC values for these three miRNAs were 0.8333, 0.8316, and 0.8142, respectively; all of them are statistically significant ( P < 0.05 ). Conclusions. The above three miRNAs found in the serum exosomes from gastric cancer patients might serve as diagnostic biomarkers for gastric cancer.