A model recommendation is useful only when it connects a real task to a complete system and a clear acceptance test.
Why model lists are not enough
A model website can tell you what files exist. It cannot know whether the model fits your computer, task, privacy rules, users, or waiting-time needs.
A leaderboard can show one type of test. It does not prove that the winner will complete your private business task on your hardware.
Describe the job first
- What information goes in?
- What useful result must come out?
- How many people will use it?
- How fast must the answer arrive?
- Must everything remain local?
- What happens when the answer is wrong?
- What hardware budget is available?
Build three honest choices
A minimum plan should prove the idea at low cost. A recommended plan should handle normal daily work. A professional plan should add capacity, control, monitoring, and recovery for serious use.
Each plan should name the model, engine, RAM, GPU class, storage, supporting software, limits, and tests. A model name alone is not a system plan.
Use confidence, not false certainty
A recommendation should explain what is known and what remains uncertain. Complex agents, regulated data, many users, and large purchases need a human check.
Good recommendation tools can refuse to make a confident choice when the evidence is weak.
Saying what is not known is more useful than pretending every setup will work.
Validate before buying
- Run the smallest useful test first.
- Use real examples and a written pass mark.
- Measure quality, speed, memory, and failures.
- Check licenses and official engine support.
- Buy hardware only after the test shows a clear need.
Official references used
These primary sources support the technical concepts in this guide. Product behavior changes, so verify the current documentation before deployment.
Find a model your computer can run.
The LocalLens advisor applies conservative memory rules and tells you when the evidence is insufficient.
Run the free compatibility check →This guide is educational and reviewed for practical accuracy. Model software, licenses and hardware support change; verify official sources before a production deployment.