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Can the Apple M3 Pro (36GB) run Qwen3.8 27B?

Apple M3 Pro (36GB) × Qwen3.8 27B8K context
YesRuns fully on the GPU
Memory at Q6_K23.9 GB of 24.1 GB
Weights 22.8 GBKV cache 0.5 GBRuntime 0.6 GB
QuantQ6_KExcellent
Speed~4tokens per second
Max context9Ktokens that fit at Q6_K
  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 M3 Pro (36GB) can run Qwen3.8 27B fully in unified memory at Q6_K (excellent), using about 23.9 GB of the 24.1 GB available, at roughly 4 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Qwen3.8 27B:

ollama run qwen3.8:27b

Ollama's default download is Q4_K_M (about 18 GB here). You have room for Q6_K, which is excellent: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the Apple M3 Pro (36GB)

Run it in the cloud

No Apple M3 Pro (36GB)? Run Qwen3.8 27B 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 24.1 GB the Apple M3 Pro (36GB) can use. macOS lets the GPU use about 24.1 GB of the 36 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality56.7 GBToo big—
Q8_0Near-lossless30.7 GBToo big—
Q6_KExcellent23.9 GBFits~4 tok/s
Q5_K_MVery good20.9 GBFits~5 tok/s
Q4_K_MGood, most popular18 GBFits~5 tok/s
Q3_K_MNoticeably degraded14.7 GBFits~7 tok/s
Q2_KHeavily degraded11.6 GBFits~9 tok/s

Measured speed from real Apple M3 Pro (36GB) owners

Tokens per second that people measured on their own Apple M3 Pro (36GB), next to our estimate.

No one has measured Qwen3.8 27B on the Apple M3 Pro (36GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M3 Pro (36GB)? Add your real speed

One command times Qwen3.8 27B 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 -- qwen3.8:27b

Windows (PowerShell)

$env:GPUFIT_MODEL="qwen3.8:27b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Qwen3.8 27B comfortably

Models that run well on the Apple M3 Pro (36GB)

Frequently asked questions

Can Apple M3 Pro (36GB) run Qwen3.8 27B?

Yes. The Apple M3 Pro (36GB) can run Qwen3.8 27B fully in unified memory at Q6_K (excellent), using about 23.9 GB of the 24.1 GB available, at roughly 4 tokens/second.

How much VRAM does Qwen3.8 27B need?

About 18 GB at Q4_K_M with 8,192 tokens of context, and about 56.7 GB at full FP16 precision.

How fast is Qwen3.8 27B on the Apple M3 Pro (36GB)?

Roughly 4 tokens per second at Q6_K, estimated from the Apple M3 Pro (36GB)'s 150 GB/s memory bandwidth.