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How to run local open models faster on your own hardware with Magnitude

Install Magnitude so each model's kernels are tuned for your chip when you download it.

Short answer: Install with curl -fsSL https://magnitude.dev/install.sh | sh, or the Windows PowerShell or desktop installer; then open the app or CLI and download a model; tuning happens on download; run the same prompt you used in Ollama and compare speed. All steps.

Remote script. The quick install pipes a script into sh; the desktop installers are an alternative.

Who it is forA local AI user on a Mac or NVIDIA PC who finds Ollama or LM Studio slow.

The problemGeneric one-size-fits-all kernels leave speed on the table on any specific chip.

The outcomeModels running locally with kernels tuned for your hardware and a built-in speculative decoding drafter.

What you need first

  • macOS, Windows or Linux (x64 or ARM64)
  • Apple Silicon, NVIDIA, AMD or Intel GPU, or a CPU only
  • Enough memory for the model you choose

Steps

  1. Install with curl -fsSL https://magnitude.dev/install.sh | sh, or the Windows PowerShell or desktop installer
  2. Open the app or CLI and download a model; tuning happens on download
  3. Run the same prompt you used in Ollama and compare speed
  4. Nothing leaves your machine and there are no token costs

Prompt for your agent

Install magnitudedev/magnitude on this <machine>, download <model>, and compare tokens per second against my current <Ollama or LM Studio> setup on the same prompt.

Caveat. This card is written from the magnitudedev/magnitude README, not from a test run by Deduped. Before you start, make sure you have macOS, Windows or Linux. Check the repo for newer instructions before you rely on these steps.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for magnitudedev/magnitude and "Run local open models faster on your own hardware"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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