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How to Run Qwen Locally with Ollama

A practical guide to installing Ollama, choosing a Qwen tag, running Qwen locally, checking GPU use, and enabling image input.
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To run Qwen locally, install Ollama, choose a Qwen model tag that fits your task, then run ollama run <model-tag>. The first run downloads that model. Use ollama ps while it is loaded to see whether Ollama placed it on the GPU, CPU, or both.

How do I install Ollama?

Get the installer for your operating system from Ollama’s download page. Its listed terminal commands are:

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  • macOS or Linux: curl -fsSL https://ollama.com/install.sh | sh
  • Windows PowerShell: irm https://ollama.com/install.ps1 | iex

The page also offers manual installers. These commands and available downloads can change, so use the current official page if an installer command fails.

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Which Qwen model can my computer run?

Choose a model by what you need it to do and how much memory your computer can make available. The Qwen3 library includes text models in several sizes, while the Qwen3.5 library lists text-and-image variants. Tags and listed download sizes below are examples from the live Ollama library listings, not minimum RAM or VRAM requirements.

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Model family and example tag Capability Listed download size
Qwen3:0.6b Text 523 MB
Qwen3:14b Text 9.3 GB
Qwen3:30b Text 19 GB
Qwen3:235b Text 142 GB
Qwen3.5:0.8b Text and image 1.2–1.3 GB
Qwen3.5:9b Text and image 6.6–7.6 GB
Qwen3.5:122b Text and image 81 GB

These are download sizes shown by Ollama’s live model listings, accessed October 7, 2026; they are not a dated benchmark or a promise that a model will fit in a particular amount of system or GPU memory. Runtime memory use also depends on context length and concurrent requests. Larger models may run slowly without a strong GPU, and actual speed depends on the computer and workload. The listings do not establish a universal minimum GPU or RAM amount.

For a first trial, select a smaller tag from the relevant library, then try a larger one if it meets your needs and runs acceptably on your machine. Check the listing for the exact tag, capabilities, download size, and available context options before downloading.

How do I run Qwen in Ollama?

Open a terminal or PowerShell window after installing Ollama, then use a tag from its library page. For example:

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ollama run qwen3
ollama run qwen3:30b

For Qwen3.5, the library’s example command is:

ollama run qwen3.5

Use one command at a time. Ollama downloads the selected model if it is not already available locally, then opens an interactive prompt where you can enter a request. To leave the interactive session, use /bye.

Ollama also documents a local chat API at http://localhost:11434/api/chat, with Python and JavaScript client examples on the model pages. That endpoint is for applications on your machine; use the relevant library page to match its example to the model tag you selected.

How do I check whether Ollama is using my GPU?

With the model loaded, open another terminal and run:

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ollama ps

Read the PROCESSOR column. Ollama reports whether the model is placed on the GPU, CPU, or split between them. A model can run without being entirely on the GPU, but its speed will depend on the hardware, model placement, and workload. The output is a placement check, not a speed benchmark.

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How do I change Qwen’s context length?

Ollama’s FAQ documents a default context window of 4096 tokens. That runtime default is distinct from a model listing’s advertised context length. Increasing the context can use more memory, as can handling concurrent requests.

To set the context length in the interactive session, enter a value such as:

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/set parameter num_ctx 4096

Alternatively, configure the server when starting it. For example, on macOS or Linux:

OLLAMA_CONTEXT_LENGTH=8192 ollama serve

For applications using the API, Ollama documents a num_ctx option in the request. Choose a context appropriate to the task and the memory available; a larger setting does not guarantee faster or better results.

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How do I use Qwen with images in Ollama?

Use a vision-capable tag rather than assuming every Qwen model accepts image input. Ollama’s Qwen3-VL listing identifies its models as text-and-image and states that Qwen3-VL requires Ollama 0.12.7. Its example command is:

ollama run qwen3-vl:8b

The Qwen3.5 listing also includes text-and-image variants. Before troubleshooting an image prompt, check that the selected tag supports images and that your installed Ollama version meets the requirement shown on that model’s page.

Official references

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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