Zhipu on NVIDIA Blackwell

Can I run GLM-4 9B on an RTX 5080?

Yes. GLM-4 9B at Q4_K_M uses 6.5 GB of the 14.2 GB available on a RTX 5080, and runs at about 111 tokens per second. You can push the context to 128K.

Runs comfortably

6.5 GB of 14.2 GB · 46%
014 GB
Weights 5.4 GB
KV cache 0.3 GB
Runtime overhead 0.8 GB

GLM-4 9B at Q4_K_M leaves 7.7 GB spare on a RTX 5080. There is room to raise the context length or move up a quantisation level.

Generation111tok/s
Prompt processing2502tok/s
Max context128Ktokens
KV per 1K tokens0GB

Every quantisation of GLM-4 9B on a RTX 5080

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 17.5 GB 18.6 GB Won't fit — 7.38
INT8 / W8A8 8.50 9.0 GB 10.2 GB Runs comfortably 113K 68.0
Q8_0 (GGUF) 8.50 9.0 GB 10.2 GB Runs comfortably 113K 68.0
FP8 (E4M3) 8.00 8.8 GB 9.9 GB Runs comfortably 119K 70.0
Q6_K 6.56 7.2 GB 8.3 GB Runs comfortably 128K 84.7
AWQ 4-bit 4.25 6.3 GB 7.5 GB Runs comfortably 128K 95.3
GPTQ 4-bit 4.25 6.3 GB 7.5 GB Runs comfortably 128K 95.3
MXFP4 4.25 6.3 GB 7.5 GB Runs comfortably 128K 95.3
Q5_K_M 5.67 6.2 GB 7.3 GB Runs comfortably 128K 97.4
Q5_K_S 5.52 6.0 GB 7.2 GB Runs comfortably 128K 99.9
Q4_K_M 4.85 5.4 GB 6.5 GB Runs comfortably 128K 111
Q4_K_S 4.58 5.1 GB 6.3 GB Runs comfortably 128K 116
Q4_0 4.55 5.1 GB 6.2 GB Runs comfortably 128K 117
IQ4_XS 4.25 4.8 GB 6.0 GB Runs comfortably 128K 123
Q3_K_M 3.91 4.5 GB 5.6 GB Runs comfortably 128K 132
IQ3_M 3.70 4.3 GB 5.4 GB Runs comfortably 128K 137
IQ3_XXS 3.06 3.7 GB 4.8 GB Runs comfortably 128K 158
Q2_K 2.63 3.3 GB 4.4 GB Runs comfortably 128K 176
IQ2_XXS 2.06 2.8 GB 3.9 GB Runs comfortably 128K 207
IQ1_M 1.75 2.5 GB 3.6 GB Runs comfortably 128K 229

Also worth checking

GLM-4 9B on every GPU
Full hardware tableEverything that runs on a RTX 5080
Full model tableWhy the KV cache is the part that bites
Guide