Context: Ollama is a tool for running large language models directly on your own machine, instead of calling a hosted API. llama3.2:1b refers to Meta's Llama 3.2 model at 1 billion parameters — "parameters" being roughly the number of tunable values inside the model that determine what it's learned. 1 billion is small by LLM standards (production-grade models often run into the hundreds of billions), which is exactly why it's a good fit for testing on a laptop or Mac mini: fast to download, fast to load, and light enough to actually watch its resource usage in real time.
Ran: Installed Ollama, pulled llama3.2:1b, and loaded it with a prompt to force it into memory.
Result: ollama ps reported 1.5 GB for the loaded model. Breaking that down with ps aux, the actual llama-server process held 1.24 GB RSS, with the background ollama serve daemon adding a separate ~22 MB. The ollama ps figure (1.5 GB) runs a bit higher than raw process RSS — likely accounting for GPU-resident memory that doesn't show up the same way in ps. Worth noting: this was captured after the model was already loaded, not before, so it's a snapshot rather than a true before/after delta.
Takeaway: ~1.25 GB of process RSS plus GPU memory overhead is the real number to size a resources.requests.memory floor around for this model — not the ~1.3 GB download size, which undercounts the actual runtime footprint.
$ ollama ps
NAME ID SIZE PROCESSOR CONTEXT UNTIL
llama3.2:1b baf6a787fdff 1.5 GB 100% GPU 4096 About a minute from now
$ ps aux | grep ollama
flyers 95443 0.1 7.7 436962064 1295248 ?? S llama-server --model ... -c 4096
flyers 1456 0.0 0.1 436899728 22336 ?? S ollama serve
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