Can the NVIDIA RTX 3080 Ti run GLM-5.3?

RTX 3080 Ti × GLM-5.38K context
NoDoes not fit in memory
Memory at Q4_K_M457.8 GB of 12 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 3080 Ti has 12 GB usable. You could offload some layers to system RAM, but it will be very slow.

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 12 GB the NVIDIA RTX 3080 Ti 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 3080 Ti owners

Tokens per second that people measured on their own NVIDIA RTX 3080 Ti, next to our estimate.

No one has measured GLM-5.3 on the NVIDIA RTX 3080 Ti yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 3080 Ti? 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 3080 Ti run GLM-5.3?

No. Even at Q4_K_M, GLM-5.3 needs about 457.8 GB, but the NVIDIA RTX 3080 Ti has 12 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 3080 Ti?

It does not fit in the NVIDIA RTX 3080 Ti's memory, so most layers would run from system RAM and generation would be very slow.