Text / WORKFLOW

Run a private reasoning assistant with DeepSeek R1 · 14B

Run DeepSeek R1 14B privately with Ollama. Start the documented package, try a known reasoning problem, and check the answer before using it for harder work.

EstimatedSource checked 9/29/2026
LOCALRENTED GPU
Freshness 8 out of 100. Repository age: 658 days old, Jan 20, 2025. Measures age, not quality.
Popularity 72 out of 100. 196,942 downloads in 30 days; 739 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 9.0 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.

MachineDeepSeek R1 · 14B
NVIDIA GPU · 8 GBUse CPU offload with 24 GB RAM; slow.
NVIDIA GPU · 12 GBRuns at 4K text context; limited headroom.
NVIDIA GPU · 16 GBRuns at 4K with headroom; speed not tested.
NVIDIA GPU · 24 GBRuns at 4K with headroom; speed not tested.
NVIDIA GPU · 32 GBRuns at 4K with headroom; speed not tested.
AMD Radeon · 8 GBUse CPU offload with 24 GB RAM; slow. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 16 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 24 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
AMD Radeon · 32 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 8 GBUse CPU offload with 24 GB RAM; slow. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 16 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 24 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Intel Arc · 32 GBRuns at 4K with headroom; speed not tested. Confirm the Ollama GPU backend with ollama ps.
Apple Silicon · 16 GB unifiedNeeds more unified memory at 4K; use a 24 GB Mac or lower-memory model.
Apple Silicon · 24 GB unifiedRuns at 4K text context; limited memory headroom.
Apple Silicon · 32 GB unifiedRuns at 4K text context with room to raise context; speed not tested.
Apple Silicon · 64 GB unifiedRuns at 4K text context with room to raise context; speed not tested.
CPU-only · 16 GB RAMBelow the 24 GB system-RAM starting point; choose a smaller model.
CPU-only · 32 GB RAMCan run in system RAM at 4K; expect slower replies than GPU.
CPU-only · 64 GB RAMCan 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

Run a private reasoning assistant with DeepSeek R1 · 14B, step by step.

Run DeepSeek R1 14B privately with Ollama. Start the documented package, try a known reasoning problem, and check the answer before using it for harder work.

Choose a package Run its commands Check the result
01
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

DeepSeek R1 · 14B · official

The 9.0 GB published Ollama download is smaller than total runtime memory. Start with 4K text context. 12 GB GPU memory or 24 GB unified Mac memory is an estimated full-load starting point; 16 GB GPU or 32 GB Mac leaves more headroom. Longer context and other apps increase memory use; check ollama ps for actual offload.

Freshness 8 out of 100. Repository age: 658 days old, Jan 20, 2025. Measures age, not quality.
Popularity 72 out of 100. 196,942 downloads in 30 days; 739 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
View weight source
02
THE WORKFLOW

Set up DeepSeek R1 · 14B 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.

01

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
02

Check Ollama in Terminal

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

ollama --version
03

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 deepseek-r1:14b
04

Solve and verify one reasoning task

At the Ollama chat prompt, paste: “Three printers make 12 labels in 3 minutes. At the same rate, how many labels can six printers make in 15 minutes? Show the calculation.” The correct result is 120 labels: 12 labels per nine printer-minutes, multiplied by 90 printer-minutes. This checks the actual selected model, not just that its download completed.

05

Confirm the local package

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

ollama list
03
SUCCESS CHECK · DeepSeek R1 · 14B

Check the worked answer

Run the exact prompt in the operating-system instructions. The correct result is 120 labels: 12 labels per nine printer-minutes, multiplied by 90 printer-minutes. 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

Ollama cannot download or start the 14B package

Check your Ollama installation, network connection, and free disk space. The package is about 9 GB; run the exact model command again after fixing the issue.

The model is too slow or runs out of memory

Close memory-heavy applications and begin with a short context. Use a machine with more memory or a suitable rented GPU if it still does not respond comfortably.

The answer looks plausible but is wrong

Use a problem with a known result, check the intermediate arithmetic, and treat the model’s reasoning as a draft rather than proof.

REFERENCE LIBRARY

Sources and files

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

5 SOURCES

The model behind this workflow

DeepSeek R1 · 14B

Keep exploring

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Freshness 37 out of 100. Release age: 255 days old, Feb 27, 2026. Measures age, not quality.
Popularity 91 out of 100. 6,335,106 downloads in 30 days; 2,331 lifetime likes. Checked Nov 8, 2026. Measures adoption, not quality.
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Freshness 69 out of 100. Repository age: 96 days old, Aug 5, 2026. Measures age, not quality.
Popularity 96 out of 100. 7,668,187 downloads in 30 days; 19,373 lifetime likes. Checked Nov 8, 2026. Measures adoption, not quality.
Arena Open Source Web coding: rank 12 of 62. Ranked model: Qwen3.8-27B. Original model ranking, not a benchmark of this package. Export dated Nov 6, 2026. Source checked Nov 8, 2026. Human preference ranking, not hardware suitability.+3
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Popularity 77 out of 100. 436,763 downloads in 30 days; 1,098 lifetime likes. Checked Nov 8, 2026. Measures adoption, not quality.
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Run a private reasoning assistant with DeepSeek R1 · 14B | YouRunAI