LLM VRAM Calculator
Calculate how much VRAM any LLM needs to run locally — pick a model (Llama, Gemma, Qwen, DeepSeek, or search Hugging ...
What LLM VRAM Calculator does
The LLM VRAM Calculator helps users determine the video memory needed to run specific Large Language Models locally. By selecting a model from popular families like Llama, Gemma, Qwen, or DeepSeek, or by searching Hugging Face, users can choose a quantization level and context size to get an instant estimate. The output indicates which consumer or professional GPUs can accommodate the model, including support for multi-GPU configurations. This makes it possible to assess hardware feasibility before downloading or running a model. The site focuses on providing a straightforward calculation based on model parameters and user-defined settings, removing guesswork from the hardware planning process.
How to use the Inventive HQ LLM VRAM Calculator
- 1
Select a model from the dropdown or search Hugging Face for a specific LLM
- 2
Choose a quantization level to adjust the model size and precision
- 3
Set the desired context length for the calculation
- 4
View the list of compatible GPUs, with options for single or multi-GPU setups
- 5
Check the estimated VRAM requirement displayed alongside GPU compatibility
Best for
Developers and hobbyists planning to run LLMs locally who need to verify GPU compatibility and VRAM requirements before committing to a model.
Limitations
- Results are estimates based on selected quantization and context size
- Actual VRAM usage may vary depending on the specific model implementation
- Multi-GPU setups require additional hardware and configuration beyond the calculator's output
LLM VRAM Calculator FAQ
- How accurate is the VRAM estimate for running a model locally?
- The estimate is based on the model size, quantization level, and context length you select; actual usage may differ slightly depending on the model's architecture and optimization.
- Can I use this calculator for any LLM available on Hugging Face?
- Yes, the tool includes a search function for Hugging Face models, allowing you to calculate VRAM needs for a wide range of publicly available LLMs.
- What quantization options are typically available, and how do they affect VRAM?
- Quantization reduces model size and precision; lower quantization levels require less VRAM but may impact output quality, while higher levels increase VRAM usage for better fidelity.
- Does the calculator support running models across multiple GPUs?
- The tool provides compatibility information for multi-GPU setups, indicating whether a model can be distributed across available graphics cards.