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Estimate whether an LLM fits on your GPU, multi-GPU setup, or Mac.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "FitLLM" MCP server from askskill: Run: claude mcp add --transport http 'run-fitllm-fitllm' 'https://fitllm.run/api/mcp'
Developers or DevOps engineers can use it before deployment to determine whether a model fits on existing GPUs or multi-GPU hardware, reducing trial and error. It is suited for read-only capacity estimation and planning.
When a team is deciding between single-GPU, multi-GPU, and Mac setups, it can use this tool to compare VRAM usage and KV-cache impact across options. This makes it easier to narrow down viable configurations early.
Researchers evaluating the runtime requirements of different model sizes can use it to inspect exact VRAM and KV-cache calculations. It helps quickly determine whether available hardware is sufficient for experiments.
It determines whether a large language model can fit on your GPU, multi-GPU rig, or Mac, and provides exact VRAM and KV-cache calculations. It is a read-only tool.
Based on the provided information, it targets capacity estimation for a single GPU, multi-GPU setups, and Macs. For more specific compatibility details, see the source repository.
The provided material does not include installation steps, runtime requirements, or API key details. Please see the source repository for prerequisites.
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