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Can the Apple M1 (16GB) run Gemma 4 12B?

Apple M1 (16GB) × Gemma 4 12B8K context
YesRuns fully on the GPU
Memory at Q5_K_M9.5 GB of 10.7 GB
Weights 8.5 GBKV cache 0.4 GBRuntime 0.6 GB
QuantQ5_K_MVery good
Speed~5tokens per second
Max context151Ktokens that fit at Q5_K_M
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The Apple M1 (16GB) can run Gemma 4 12B fully in unified memory at Q5_K_M (very good), using about 9.5 GB of the 10.7 GB available, at roughly 5 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Gemma 4 12B:

ollama run gemma4:12b

Ollama's default download is Q4_K_M (about 8.3 GB here). You have room for Q5_K_M, which is very good: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the Apple M1 (16GB)

Run it in the cloud

No Apple M1 (16GB)? Run Gemma 4 12B in the cloud.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Rent a GPU on RunPodRent a GPU on Vast.ai

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 10.7 GB the Apple M1 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality24.9 GBToo big—
Q8_0Near-lossless13.7 GBToo big—
Q6_KExcellent10.8 GBToo big—
Q5_K_MVery good9.5 GBFits~5 tok/s
Q4_K_MGood, most popular8.3 GBFits~6 tok/s
Q3_K_MNoticeably degraded6.8 GBFits~7 tok/s
Q2_KHeavily degraded5.5 GBFits~9 tok/s

Measured speed from real Apple M1 (16GB) owners

Tokens per second that people measured on their own Apple M1 (16GB), next to our estimate.

No one has measured Gemma 4 12B on the Apple M1 (16GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M1 (16GB)? Add your real speed

One command times Gemma 4 12B 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 -s -- gemma4:12b

Windows (PowerShell)

$env:GPUFIT_MODEL="gemma4:12b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Gemma 4 12B comfortably

Models that run well on the Apple M1 (16GB)

Frequently asked questions

Can Apple M1 (16GB) run Gemma 4 12B?

Yes. The Apple M1 (16GB) can run Gemma 4 12B fully in unified memory at Q5_K_M (very good), using about 9.5 GB of the 10.7 GB available, at roughly 5 tokens/second.

How much VRAM does Gemma 4 12B need?

About 8.3 GB at Q4_K_M with 8,192 tokens of context, and about 24.9 GB at full FP16 precision.

How fast is Gemma 4 12B on the Apple M1 (16GB)?

Roughly 5 tokens per second at Q5_K_M, estimated from the Apple M1 (16GB)'s 68 GB/s memory bandwidth.