Workflows/Set up private chat with Gemma 4 · 12B

Text / WORKFLOW

Set up private chat with Gemma 4 · 12B

Run a private local chat with Gemma 4 · 12B using Ollama on Windows, macOS, or Linux. You will install the runtime, fetch the 7.6 GB text-and-image model package, start a chat session, send a first prompt, and confirm the model responds.

EstimatedSource checked 9/29/2026

LOCALRENTED GPU

Freshness 52 out of 100. Repository age: 170 days old, May 23, 2026. Measures age, not quality.

Popularity 84 out of 100. 1,814,143 downloads in 30 days; 1,728 lifetime likes. Checked Nov 8, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source

Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Nov 9, 2026. Statistics checked Nov 8, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

Before you begin

Hardware

Estimates for the 7.6 GB Ollama package at 4K text context. A full GPU load needs room beyond the weight download for runtime and KV cache; CPU offload can run on smaller GPUs with enough system RAM, but responds more slowly.

Machine	Gemma 4 · 12B
NVIDIA GPU · 8 GB	Use CPU offload with 24 GB RAM; slow.
NVIDIA GPU · 12 GB	Runs at 4K text context; limited headroom.
NVIDIA GPU · 16 GB	Runs at 4K with headroom; speed not tested.
NVIDIA GPU · 24 GB	Runs at 4K with headroom; speed not tested.
NVIDIA GPU · 32 GB	Runs at 4K with headroom; speed not tested.
AMD Radeon · 8 GB	Use CPU offload with 24 GB RAM; slow. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 16 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 24 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 32 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 8 GB	Use CPU offload with 24 GB RAM; slow. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 16 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 24 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 32 GB	Runs at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Apple Silicon · 16 GB unified	Runs at 4K text context; limited memory headroom.
Apple Silicon · 24 GB unified	Runs at 4K text context with room to raise context; speed not tested.
Apple Silicon · 32 GB unified	Runs at 4K text context with room to raise context; speed not tested.
Apple Silicon · 64 GB unified	Runs at 4K text context with room to raise context; speed not tested.
CPU-only · 16 GB RAM	Below the 24 GB system-RAM starting point; choose a smaller model.
CPU-only · 32 GB RAM	Can run in system RAM at 4K; expect slower replies than GPU.
CPU-only · 64 GB RAM	Can run in system RAM at 4K; expect slower replies than GPU.

These are memory-fit starting points, not performance tests. Check the exact AMD or Intel Ollama backend and use ollama ps to see the GPU/CPU split; longer context or image input needs more memory.

TEXT / OLLAMASOURCE-LINKED SETUP

Set up private chat with Gemma 4 · 12B, step by step.

Choose a package Run its commands Check the result

BEFORE YOU BEGIN

The documented package

This setup uses the package documented for this task. Review its source and supported platforms before starting.

Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.

CURRENT SETUP

Gemma 4 · 12B · official

The 7.6 GB published Ollama download is smaller than total runtime memory. Start with 4K text context. 12 GB GPU memory or 16 GB unified Mac memory is an estimated full-load starting point; 16 GB GPU or 24 GB Mac leaves more headroom. Longer context and other apps increase memory use; check ollama ps for actual offload.

Freshness 52 out of 100. Repository age: 170 days old, May 23, 2026. Measures age, not quality.

Popularity 84 out of 100. 1,814,143 downloads in 30 days; 1,728 lifetime likes. Checked Nov 8, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

Check the date source

Popularity · adoption

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Nov 9, 2026. Statistics checked Nov 8, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

View weight source

THE WORKFLOW

Set up Gemma 4 · 12B on your machine

Choose where you want to run it. The instructions below update to match your selection.

CHOOSE YOUR SETUPMac

Use Terminal on Apple Silicon. Ollama for macOS is available from the official download page.

Install Ollama for macOS

Download the Mac application from Ollama, move it to Applications, and open it so the local service starts.

Download Ollama for Mac

Check Ollama in Terminal

Open a new Terminal window and confirm the command-line tool is available.

ollama --version

Download and start this exact package

Run the publisher-listed command. The first launch downloads the selected weights; subsequent launches reuse the local copy.

ollama run gemma4:12b

Run and inspect a real local task

At the Ollama chat prompt, paste: “Write a four-step plan for digitizing family photos. Include a second backup and a way to keep private photos private.” The four steps should cover scanning, organizing, a second copy and access controls. This checks the actual selected model, not just that its download completed.

Confirm the local package

In a second Terminal window, verify that the selected package is installed locally.

ollama list

SUCCESS CHECK · Gemma 4 · 12B

Check the local result

Run the exact prompt in the operating-system instructions. The four steps should cover scanning, organizing, a second copy and access controls. Confirm that Ollama lists the selected package and use ollama ps to check whether it ran on GPU or fell back to CPU.

This is a source-linked setup, not a YouRunAI hardware test. Confirm your exact runtime version, package, and output before relying on it.

Back to setup steps

When it doesn’t go to plan

The ollama command is not recognized after installation.

Open a fresh terminal window so the updated PATH is loaded, then run the install step again if needed.

The model pull stops or fails before finishing.

Check that the 7.6 GB package fits on your disk and that your connection is stable, then run ollama run gemma4:12b again to resume or retry the download.

The model loads slowly or the machine runs out of memory.

Close other memory-heavy applications before starting Gemma 4 · 12B, and avoid combining image input or long context unless the machine has memory to spare.

REFERENCE LIBRARY

Sources and files

Original instructions, model files, and compatibility notes behind this setup.

5 SOURCES

01Publisher model card and weightshuggingface.co 02Publisher run instructionsollama.com 03Official Ollama downloadollama.com 04Ollama CLI referencedocs.ollama.com 05Ollama GPU and driver supportdocs.ollama.com

The model behind this workflow

Gemma 4 · 12B

Keep exploring

Text

SETUP GUIDE

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Freshness 32 out of 100. Release age: 298 days old, Jan 15, 2026. Measures age, not quality.

SOFTWAREComfyUI

LOCALRENTED GPU

Verified source