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HomeCan I run it?GLM-4.5-AirGLM-4.5-Air on an RTX 5090

No. GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and the GeForce RTX 5090 has 32.0 GB usable at a ~4k context.

Can I run GLM-4.5-Air on an RTX 5090?

GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and the GeForce RTX 5090 has 32.0 GB usable. That figure is 32 GB of VRAM on the spec sheet, of which 32.0 GB is usable for weights and cache, at 1792 GB/s memory bandwidth. Zhipu’s GLM-4.5-Air, a large model in the roughly 80 GB Q4 class — above a 24 GB card, below full DeepSeek-R1. These are estimates from our formula, not measured benchmarks.

Quant that fits
None of Q4, Q8 or FP16 needs 78.0 GB
Memory needed
78.0 GB at Q4_K_M, ~4k context
Usable VRAM
32.0 GB of 32 GB VRAM
Est. tokens/sec
n/a does not fit

GLM-4.5-Air · GeForce RTX 5090 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 32.0 GBVerdict
Q4_K_M78.0 GBQ4Won’t fit
Q8_0136.0 GBQ8Won’t fit
FP16255.1 GBFP16Won’t fit

Estimated tokens per second

No speed estimate: GLM-4.5-Air does not fit in the 32.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.

Context headroom

Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.

Context headroom for GLM-4.5-Air on an RTX 5090 at Q4_K_M
ContextKV cache (FP16)Total at Q4_K_MVerdict
4k0.8 GB78.0 GBWon’t fit
8k1.5 GB78.8 GBWon’t fit
16k3.1 GB80.3 GBWon’t fit
32k6.2 GB83.4 GBWon’t fit
64k12.3 GB89.6 GBWon’t fit
128k24.7 GB101.9 GBWon’t fit

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

Other hardware for GLM-4.5-Air

Other models on an RTX 5090

Quick answers

Can I run GLM-4.5-Air on an RTX 5090?
No. GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and the GeForce RTX 5090 has 32.0 GB usable.
How much VRAM does GLM-4.5-Air need?
About 78.0 GB at Q4_K_M, 136.0 GB at Q8_0 and 255.1 GB at FP16, estimated for a ~4k context.
How fast is GLM-4.5-Air on an RTX 5090?
We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
What context length can I use?
The weights already do not fit, so longer context is not the limiting factor.

New models, and what they need to run

One short email a week: fresh open models with their VRAM numbers, plus hardware worth watching.