Can the NVIDIA RTX 4060 run GLM-5.3?

RTX 4060 × GLM-5.38K context
NoDoes not fit in memory
Memory at Q4_K_M457.8 GB of 8 GB
Weights 456.5 GBKV cache 0.7 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, GLM-5.3 needs about 457.8 GB, but the NVIDIA RTX 4060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

Run it in the cloud

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 8 GB the NVIDIA RTX 4060 can use.

QuantQualityMemoryFits?Speed
FP16Full quality1507.3 GBToo big—
Q8_0Near-lossless801.4 GBToo big—
Q6_KExcellent618.8 GBToo big—
Q5_K_MVery good536.9 GBToo big—
Q4_K_MGood, most popular457.8 GBToo big—
Q3_K_MNoticeably degraded369.4 GBToo big—
Q2_KHeavily degraded283.7 GBToo big—

Measured speed from real RTX 4060 owners

Tokens per second that people measured on their own NVIDIA RTX 4060, next to our estimate.

No one has measured GLM-5.3 on the NVIDIA RTX 4060 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 4060? Add your real speed

One command times GLM-5.3 in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh

Windows (PowerShell)

irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

Frequently asked questions

Can NVIDIA RTX 4060 run GLM-5.3?

No. Even at Q4_K_M, GLM-5.3 needs about 457.8 GB, but the NVIDIA RTX 4060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does GLM-5.3 need?

About 457.8 GB at Q4_K_M with 8,192 tokens of context, and about 1507.3 GB at full FP16 precision.

How fast is GLM-5.3 on the NVIDIA RTX 4060?

It does not fit in the NVIDIA RTX 4060's memory, so most layers would run from system RAM and generation would be very slow.