GPU for Model Recommender
Find the cheapest GPU that can run the local LLM you want. Recommends hardware by required VRAM, quantization, and ta...
What GPU for Model Recommender does
This tool helps users determine the minimum graphics hardware needed to run a specific local large language model. By selecting a model from an extensive list, the system calculates the cheapest GPU that can handle the task, factoring in the model's required VRAM, the quantization level, and the intended context length. The output identifies the baseline card for smooth operation, cards that can run the model with performance trade-offs, and cards that cannot meet the requirements. It serves as a practical hardware compatibility checker for anyone planning to run open-source models on their own system.
How to use the Wide Area AI GPU for Model Recommender
- 1
Open the GPU Picker interface on the site.
- 2
Select the desired large language model from the dropdown list.
- 3
Review the ranked GPU options showing minimum requirements and estimated speed.
- 4
Choose a card based on whether you want the minimum viable hardware or better performance.
- 5
Check the displayed memory needs and token-per-second estimates for your setup.
Best for
This option suits developers, hobbyists, and researchers who want to run specific open-source models locally and need a quick, free way to verify GPU compatibility before purchasing or allocating hardware.
Limitations
- Results are estimates based on model architecture and quantization.
- No direct purchasing or pricing data for hardware is provided.
- Performance may vary depending on system configuration and drivers.
GPU for Model Recommender FAQ
- How does the tool decide which GPU is cheapest for a model?
- 1-3 sentence answer grounded in the material
- Can I compare multiple models side-by-side to find the best GPU?
- 1-3 sentence answer grounded in the material
- Does the tool account for different quantization levels of the same model?
- 1-3 sentence answer grounded in the material
- Is the GPU data updated regularly to reflect new hardware releases?
- 1-3 sentence answer grounded in the material