Can the Apple M4 (16GB) run GLM-5.3?

Apple M4 (16GB) × GLM-5.38K context
NoDoes not fit in memory
Memory at Q4_K_M457.8 GB of 10.7 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 Apple M4 (16GB) has 10.7 GB usable. You could offload some layers to system RAM, but it will be very slow.

Run it in the cloud

Too big for the Apple M4 (16GB)? Run GLM-5.3 on a rented GPU instead.

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 10.7 GB the Apple M4 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

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 Apple M4 (16GB) owners

Tokens per second that people measured on their own Apple M4 (16GB), next to our estimate.

No one has measured GLM-5.3 on the Apple M4 (16GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M4 (16GB)? 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 Apple M4 (16GB) run GLM-5.3?

No. Even at Q4_K_M, GLM-5.3 needs about 457.8 GB, but the Apple M4 (16GB) has 10.7 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 Apple M4 (16GB)?

It does not fit in the Apple M4 (16GB)'s memory, so most layers would run from system RAM and generation would be very slow.