GLM-4.5 Air: how much VRAM it needs and which GPU runs it

GLM-4.5 Air in Q4_K_M with an 8k context takes 70.4 GB of GPU memory. The cheapest option right now is A800 PCIe 80 GB, from $0.99/h.

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VRAM by quantisation

The weight file and the total GPU memory with the context cache. One GPU, one request.

Quantisation	File	8K context	32K context	128K context	Fits on
BF16	205.8	208.3	212.6	229.9	B300 288 GB
FP8	104.8	107.3	111.6	128.9	H200 NVL 141 GB
Q8_0	109.4	111.9	116.2	133.4	H200 NVL 141 GB
Q6_K	92.2	94.7	99.0	116.2	H200 NVL 141 GB
Q5_K_M	77.8	80.3	84.6	101.8	H100 NVL 94 GB
Q4_K_M	68.0	70.4	74.8	92.0	A800 PCIe 80 GB
Q3_K_M	53.3	55.8	60.1	77.3	RTX PRO 5000 72 GB
Q2_K	42.2	44.7	49.0	66.2	RTX A6000 48 GB

Context cache

How much memory the cache takes per request in FP16. A Q8 cache is about half. 184 KB per token.

8K context: 1.4 GB
32K context: 5.8 GB
128K context: 23.0 GB

Cheapest GPUs that run it

GPUs from the catalog the model fits on, by price per hour.

A800 PCIe 80 GB90% usedfrom $0.99/hRent
2× RTX A6000 48 GB76% usedfrom $1.14/hRent
A100 PCIe 80 GB90% usedfrom $1.19/hRent
4× RTX 3090 24 GB79% usedfrom $1.21/hRent
8× RTX A4000 16 GB62% usedfrom $1.35/hRent

The price is the cheapest GPU of the model × the GPU count. A 2–8 GPU server can cost a little more per GPU.

How to run it on gpu.nz

For an API under load there is the vLLM template with an OpenAI-compatible API.

Questions

How much VRAM does GLM-4.5 Air need?: In Q4_K_M with an 8k context, 70.4 GB: weights 68.0 GB, context cache 1.4 GB and about 1 GB of runtime memory. In BF16, 208.3 GB.
Does GLM-4.5 Air run on an RTX 4090 with 24 GB?: It does not fit on one RTX 4090 even in Q4_K_M: it needs 70.4 GB. A 80 GB GB card or several RTX 4090s will do.
How much does it cost to run GLM-4.5 Air?: The cheapest fitting server right now is A800 PCIe 80 GB, from $0.99/h. Billing is per minute: stop the server and only its disk is billed.
Which quantisation should I pick?: Q4_K_M is the chat default: close to the original quality at a third of BF16's size. Q5_K_M and Q6_K are more accurate, Q8_0 is almost the original. For vLLM use FP8 or BF16.

File sizes checked against Hugging Face on 2026-10-19. 1 GB here is 1024³ bytes, like GPU memory. Hugging Face lists decimal gigabytes, so its numbers are 7% larger.

VRAM by quantisation

The weight file and the total GPU memory with the context cache. One GPU, one request.

Quantisation	File	8K context	32K context	128K context	Fits on
BF16	205.8	208.3	212.6	229.9	B300 288 GB
FP8	104.8	107.3	111.6	128.9	H200 NVL 141 GB
Q8_0	109.4	111.9	116.2	133.4	H200 NVL 141 GB
Q6_K	92.2	94.7	99.0	116.2	H200 NVL 141 GB
Q5_K_M	77.8	80.3	84.6	101.8	H100 NVL 94 GB
Q4_K_M	68.0	70.4	74.8	92.0	A800 PCIe 80 GB
Q3_K_M	53.3	55.8	60.1	77.3	RTX PRO 5000 72 GB
Q2_K	42.2	44.7	49.0	66.2	RTX A6000 48 GB

Cheapest GPUs that run it

GPUs from the catalog the model fits on, by price per hour.

A800 PCIe 80 GB90% usedfrom $0.99/hRent

2× RTX A6000 48 GB76% usedfrom $1.14/hRent

A100 PCIe 80 GB90% usedfrom $1.19/hRent

4× RTX 3090 24 GB79% usedfrom $1.21/hRent

8× RTX A4000 16 GB62% usedfrom $1.35/hRent

The price is the cheapest GPU of the model × the GPU count. A 2–8 GPU server can cost a little more per GPU.

Questions

How much VRAM does GLM-4.5 Air need?

In Q4_K_M with an 8k context, 70.4 GB: weights 68.0 GB, context cache 1.4 GB and about 1 GB of runtime memory. In BF16, 208.3 GB.

Does GLM-4.5 Air run on an RTX 4090 with 24 GB?

It does not fit on one RTX 4090 even in Q4_K_M: it needs 70.4 GB. A 80 GB GB card or several RTX 4090s will do.

How much does it cost to run GLM-4.5 Air?

The cheapest fitting server right now is A800 PCIe 80 GB, from $0.99/h. Billing is per minute: stop the server and only its disk is billed.

Which quantisation should I pick?

Q4_K_M is the chat default: close to the original quality at a third of BF16's size. Q5_K_M and Q6_K are more accurate, Q8_0 is almost the original. For vLLM use FP8 or BF16.