I Put Three AI Services on One 24 GB GPU. It Used 17.8. Here's What Fits.
A DEV Community article titled "I Put Three AI Services on One 24 GB GPU. It Used 17.8. Here's What Fits." reports placing three AI services on a single 24 GB GPU and states that the combined footprint came to 17.8 GB. That is the extent of the technical claim available in the supplied source text: the title and the figure of 17.8 GB. The body content provided is not the article's prose but the page's embedded CSS, which defines a retro visual theme for posts carrying a specific article tag, including styling for light and dark modes, card borders, headings, links, and tags. Because the excerpt contains no service names, model names, package versions, quantization settings, context lengths, throughput numbers, or hardware details beyond the 24 GB card capacity, those specifics cannot be reported. The article's own framing is a memory-budget question: how much of a 24 GB GPU is consumed when three AI services run together, and what remains. The reported 17.8 GB figure is the only quantitative value present, and it is presented in the title as the observed usage for that combination. Readers looking for the actual service list, configuration, or measurement method would need the article body, which is not included here.
The post reports a concrete memory figure for co-hosting three AI services on one 24 GB GPU, a constraint developers weigh when consolidating workloads.