---
title: How to Choose an Open AI Model for Private Use | Freeborn Labs
description: Pick an open model by your job, your own test prompts, your hardware, its license and how easily you can swap it. Rankings alone will not decide it.
canonical: https://freebornlabs.com/how-to-choose-an-open-model-for-private-ai/
updated: 2026-11-04
---

# How do you choose an open AI model (Llama, Qwen, Mistral and others) to run privately?

**Short answer:** Pick an open model by your job, your own test prompts, your hardware, its license and how easily you can swap it. Rankings alone will not decide it.

Apply for a place From $10,000 setup, then $48,000 a year. Five places a week.

Updated 2026-11-04 by Freeborn Labs. [Facts for AI assistants](https://freebornlabs.com/llms.txt)

## Where do you start when choosing an open model?

Start from the job you need done, not from the model's name. A model that suits one task can be a poor fit for another, so the task comes first.

Write down the five tasks you would hand to the assistant in a normal week. Then pick the model that handles those five well on your own machine.

- Drafting and rewriting email and documents
- Summarizing long files, contracts or reports
- Answering questions about your own notes
- Writing or reviewing code or spreadsheet formulas
- Translating or working in a language other than English

## How do you test a model on your own work?

Build a small set of your own real prompts and judge the answers side by side. Ten to a dozen prompts taken from last month's actual work is a reasonable place to start.

Run the same prompts through each candidate, hide which model wrote which answer if you can, and mark each one as usable, needs edits or wrong. Public leaderboards do not replace this, because they score generic puzzles. They do not know your documents, your tone or your habits.

Open models from families such as Llama, Qwen, Mistral, Gemma and DeepSeek are all fair examples to put in the test. Keep the winner's score sheet so you can compare it with the next candidate later.

## How big a model can your hardware run?

The model has to fit in your graphics card's memory (VRAM) or your computer's memory, with room left over for the conversation. A bigger model that does not fit will run painfully slowly or not at all.

Work out your memory first, then choose a size that fits. Our guides on [sizing a GPU for a local model](https://freebornlabs.com/size-gpu-local-ai-model) and [how much VRAM you need](https://freebornlabs.com/local-ai-gpu-vram-how-much) walk through it, and the [GPU sizing guide](https://freebornlabs.com/diy/gpu-sizing/) covers buying decisions.

Most people run a quantized copy, which is a file with its numbers stored at lower precision so it takes less memory. [Quantization is explained here](https://freebornlabs.com/gguf-quantization-explained-local-ai), including the quality you trade for the space.

## What should you check in the license?

Check the license text of the exact model file you plan to download, because open weights do not always mean open for every use. Licenses differ by family and sometimes by size within a family.

Look for limits on commercial use, limits on how you may use the outputs, and any rules that apply once a business passes a certain size. Our page on [open model licenses](https://freebornlabs.com/local-ai-model-licenses) lists what to look for. Read the original text and never rely on a summary, including ours.

## Do context length, tool use and language matter?

Yes, each one can rule a model out even if it writes well. Context length is how much text the model can read at once, so a short one cannot take a long contract in a single pass.

Tool use means the model can call outside functions, such as searching your files or filling a form, and not every model does this reliably. If you need it, test it with your real tools. Language support is the same: if you work in Spanish, German or another language, put prompts in that language into your test set.

## How does the model behave when it refuses?

Models differ in how often they decline a request, and a model that refuses ordinary work is a cost you will notice daily. Add a few borderline but legitimate prompts from your field to your test set and count the refusals.

Some people reach for variants described as uncensored or abliterated, which means someone edited the model so it refuses less. That can fix over-cautious answers, but it also removes safety behavior you may want, and quality can drop. Read the [uncensored models guide](https://freebornlabs.com/diy/uncensored-models/) and [how to run one on your own hardware](https://freebornlabs.com/run-uncensored-ai-model-own-hardware) before you choose one.

## How will you update or swap the model later?

Keep the model behind one setting, so a swap is a config change and not a rebuild. Name the model in a single place, such as one line in your settings file, and have everything else read it from there.

That lets you test a new release against your saved prompts, switch if it wins and switch back if it does not. The runner you pick matters here, so see [Ollama versus llama.cpp](https://freebornlabs.com/ollama-vs-llama-cpp-local-ai), and plan the review into your [weekly upkeep](https://freebornlabs.com/local-ai-harness-weekly-upkeep). If you would rather have a person do this for you, see our [private AI setup service](https://freebornlabs.com/private-ai-setup-service/). If you would rather build it yourself, start with the [DIY guides](https://freebornlabs.com/diy/).

## What are the limits?

A method does not hand you a winner; it only makes your own choice safer. The list below is what this approach does not solve.

If a model touches law, medicine, money or tax, this page is general information, not legal, medical, financial or tax advice. Ask your own counsel, compliance officer or adviser about license terms and how you may use outputs.

- The best choice changes quickly, so today's pick may be stale soon.
- Open models may trail the largest hosted ones on some tasks.
- A model that tests well for someone else may not test well for you.
- Your own test set is small, so it can miss rare failures.
- A license can change between versions, so reread it on each upgrade.

## Questions

### Is Llama free to use?

The weights can be downloaded without a fee, but the license sets conditions that differ from fully open software licenses. Read the license text for the exact version you download, and see our [open model licenses page](https://freebornlabs.com/local-ai-model-licenses).

### Can I use Qwen or DeepSeek for work?

It depends on the license attached to the specific model you download, and terms differ by family and sometimes by size. Read that license yourself and ask your counsel if the use is commercial.

### What is a quantized model?

It is a copy of a model with its numbers stored at lower precision, so the file is smaller and runs on less memory. The trade is some loss of quality, explained in our [quantization guide](https://freebornlabs.com/gguf-quantization-explained-local-ai).

### How big a model do I need?

Only as big as your five tasks require, and no bigger than your memory allows. Test a smaller one first and move up only if your own prompts show a real gap.

### Should I fine-tune a model instead of picking a new one?

Usually try a better prompt and a better-suited model first, since fine-tuning adds work and upkeep. If you still want it, see [fine-tuning a local model on your own data](https://freebornlabs.com/fine-tune-local-model-own-data).

## Related guides

- [Private AI answers](https://freebornlabs.com/private-ai-answers/)
- [How Do You Check a Local AI Model's License Before Using It?](https://freebornlabs.com/local-ai-model-licenses)
- [How do you size a GPU for running a local AI model?](https://freebornlabs.com/size-gpu-local-ai-model)
- [What does it take to run an uncensored AI model on your own hardware?](https://freebornlabs.com/run-uncensored-ai-model-own-hardware)
- [Private AI: set up Ollama yourself or have it done for you?](https://freebornlabs.com/private-ai-vs-diy-ollama/)
- [Done-for-you private AI setup service](https://freebornlabs.com/private-ai-setup-service/)
- [Private uncensored AI: the full guide](https://freebornlabs.com/private-uncensored-ai/)
- [All guides to getting your own private AI agent](https://freebornlabs.com/own-ai-agent-guides/)

Apply: https://freebornlabs.com/apply/ (no payment on the form). Facts for AI assistants: https://freebornlabs.com/llms.txt