The outcome

Select a model configuration that provides acceptable quality, speed, and memory use on available hardware.

Step by step

A workflow you can repeat.

  1. 01

    Record the task, languages, context size, license needs, privacy boundary, and the machine's RAM, VRAM, processor, and free storage.

  2. 02

    Search LM Studio for compatible GGUF or MLX candidates and inspect their publisher, model card, license, parameter size, and quantization.

  3. 03

    Download a realistic size, load it with a conservative context and hardware-offload setting, and confirm the app remains stable.

  4. 04

    Run the same representative, factual, and adversarial prompts while recording quality, latency, memory use, and failure patterns.

  5. 05

    Save the chosen model identifier and settings, verify offline operation if required, and retain a smaller fallback for constrained machines.

Working standard

What good use looks like.

  • Choose models for the actual hardware.
  • Evaluate several task-shaped prompts.
  • Record model and quantization exactly.

Official references

Check the current product documentation.