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One step earlier: not sure you should buy hardware at all? Our cost calculator compares buying vs renting cloud GPUs vs just paying for an API, with break-even math for your usage.
Two ways to use it: leave "Your machine" empty to shop across everything we track, or pick the hardware you already own (or enter its memory) to get a personal verdict, including, when it doesn't fit, the exact quant, context, or KV-cache change that would make it fit.
How the estimate works #
The tool uses the same math from our guides, shown in the open because that's the point of this site. A model's memory cost has three parts:
Weights, parameters × bits-per-weight ÷ 8. A 70B model at Q4_K_M (~4.8 bits/weight) is about 42 GB. Quantization choices are covered in ourplain-English quantization guide.KV cache, grows with every token of context. We assume a GQA-typical attention shape and an FP16 cache; the KV-precision selector in the tool shows exactly what a Q8 or Q4 cache saves. Full math inThe KV cache, explained.Overhead, a flat ~1.5 GB buffer for the runtime and activations.
For Mixture-of-Experts models, memory follows total parameters but speed follows active parameters, that's why a 120B MoE can be fast on a box that would crawl on a dense 70B. The one-line rule: buy memory for the total, expect speed from the active (MoE, explained). The "gen ceiling" column is memory bandwidth ÷ bytes streamed per token, a theoretical upper bound from the fact that token generation is bandwidth-bound, not compute-bound (why that is). Real speeds come in below it.
Honest limits #
These are estimates, not lab measurements. Real usage varies by runtime (llama.cpp vs vLLM vs MLX), KV-cache precision, batch settings, and model architecture. Unified-memory machines share RAM with the OS, so we subtract an 8 GB reserve; discrete GPUs lose ~1 GB to the desktop. When a result says "tight fit," believe it, within 10% of capacity means long context or background apps will push you over. Hardware listings come from our methodology; affiliate links never influence what appears or how it ranks.