GLM-4.5V

A parameters × bits ÷ 8 estimate puts I1-IQ1_S at roughly 56.43 GiB. The real file is 31.56 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

How much VRAM does GLM-4.5V need?

I1-IQ1_S is exactly 33,885,517,920 bytes (31.56 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.

How large is GLM-4.5V's KV cache?

5.75 GiB at 32K context with an f16 cache, computed per layer. Quantizing the cache to q8_0 roughly halves it, which is often the difference between a context length fitting and not.

Is GLM-4.5V a mixture-of-experts model?

Yes — 128 experts, 8 routed per token. Every expert must be resident, but only the routed ones are read per token, which is why its memory requirement and its speed behave very differently.

Which quantization of GLM-4.5V should I use?

Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.