{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "maximpri-mlxtop--spot-ollama-model-running-on-cpu",
 "repo": "maximpri/mlxtop",
 "repo_url": "https://github.com/maximpri/mlxtop",
 "repo_slug": "maximpri-mlxtop",
 "title": "Spot an Ollama model partly running on the CPU",
 "page_title": "How to spot an Ollama model partly running on the CPU with Mlxtop",
 "summary": "See which loaded Ollama models use VRAM, context size and CPU or GPU placement.",
 "who": "A developer on a PC with an NVIDIA or AMD card who runs Ollama and suspects a model is spilling onto the CPU.",
 "problem": "When part of a model sits on the CPU, generation becomes much slower, and Ollama does not make that placement obvious at a glance.",
 "outcome": "The Overview verdict names a model partly on the CPU, and the loaded model list shows its VRAM and CPU or GPU placement.",
 "steps": [
  "Install Mlxtop with the install script for Linux, or `brew install maximpri/tap/mlxtop` on macOS or Linux.",
  "Start Ollama and load a model by sending it a prompt.",
  "Run `mlxtop` and open view 1 · Overview.",
  "Read the loaded models and their CPU/GPU placement, and check the verdict line for a model partly on the CPU.",
  "Use `[` and `]` to select a GPU card if the machine has more than one."
 ],
 "agent_prompt": "Using the mlxtop repo at maximpri/mlxtop, start a loaded Ollama model on <target machine>, run `mlxtop --once`, and report the loaded model name, its VRAM use and its CPU/GPU placement. Verify the report shows the placement before you say whether the model is partly on the CPU.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "For Ollama, speed is recorded after each request completes, so live tokens per second are not shown while a reply is still streaming.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "rust",
 "requirements": [
  "macOS 11 or later on Apple Silicon, Linux (x86_64 or ARM64), or Windows (x86_64)",
  "A local LLM runtime such as oMLX, Ollama, llama.cpp or vLLM installed and able to serve a model",
  "A terminal, or Rust 1.88 or newer if you build from source"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/maximpri-mlxtop/spot-ollama-model-running-on-cpu/",
 "md": "https://dedupedai.com/use-cases/maximpri-mlxtop/spot-ollama-model-running-on-cpu/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/maximpri-mlxtop--spot-ollama-model-running-on-cpu.json",
 "api_version": "v1"
}