Quantization Memory Planner
loading math engine

Make the memory fit before the model runs.

Compare weight footprints across formats against your cluster. Fit is necessary for serving, not proof of quality or runtime success.

Hardware assumptions

Weights-only planning. Reserve space for runtime memory in the cluster capacity.

Capacity = GPU memory x count - reserve. Footprint uses decimal GB for readable comparison.

SAMPLE READY

Format runway

Load the sample and plan memory.

weight GB = parameters (trillions) x 1,000,000,000,000 x bytes / 1,000,000,000 | required GPUs = ceiling(weight GB / GPU memory)

How to read it

Quantization reduces weight footprint. A fit here only means the weights fit the stated capacity; activations, KV cache, runtime overhead, bandwidth, and accuracy remain separate questions.

Source boundary

The source supplies an illustrative hardware and parameter example. This planner does not benchmark formats, predict quality, or claim a model will serve successfully.

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