The composition of an individual’s gut microbiome is known to be essential to good health and longevity. Some compositions have been found to be protective against chronic conditions such as obesity, type 2 diabetes, and bowel cancer. Diet is a key influence on the make-up of an individual’s microbiome, yet the strength of that association is vulnerable to inter-individual variation. The present study aimed to examine the relationship between diet and microbiome metabolic capacity (MC) to lessen the potential for variability in microbiome analyses. Caecal DNA samples from four mouse strain groups (n = 40), that came from two different suppliers, were stratified into three diets (Chow, high fat diet (HFD), Ketogenic (Keto)), varying in fibre, protein, and fat compositions. These relationships were assessed through two forms of metagenomic sequencing analysis, exploring abundances of pathway-coding gene families (humann2) and enzyme-coding genes (humann2 and GraftM). Additionally, qPCR and droplet digital PCR were evaluated as potential methods to capture the MC of an individual microbiome without need for sequencing. Significant differences in MC of the microbial community existed between the diets for mucin foraging, alternative carbon source utilisation, and amino acid degradation. Whilst genome-wide metabolic analysis (humann2) was able to provide insight into pathways or genes of interest, gene-specific approaches (GraftM) provided the depth required to distinguish better between study groups. These findings reveal that the relationship between diet and microbiome is complex; whereby diet modulates the impact of genetic variation on the microbiome, as microbes with different pathways involved in mucin degradation and mechanisms of energy metabolism thrive in the nutritional landscape.