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HomeCan I run it?GLM-4.5-AirGLM-4.5-Air on dual RTX 3090s

No. GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and dual RTX 3090s have 48.0 GB usable at a ~4k context.

Can I run GLM-4.5-Air on dual RTX 3090s?

GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and dual RTX 3090s have 48.0 GB usable. Two cards add memory, not decode speed; the speed estimate uses one RTX 3090’s 936 GB/s. 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
48.0 GB of 48 GB VRAM
Est. tokens/sec
n/a does not fit

GLM-4.5-Air · GeForce RTX 3090 · Multi-GPU · Dual 3090 build · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 48.0 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No speed estimate: GLM-4.5-Air does not fit in the 48.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.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 dual RTX 3090s 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 dual RTX 3090s

Quick answers

Can I run GLM-4.5-Air on dual RTX 3090s?
No. GLM-4.5-Air at Q4_K_M needs about 78.0 GB, and dual RTX 3090s have 48.0 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 dual RTX 3090s?
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

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