Rent a GPU

Can the Apple M2 Pro (32GB) run Qwen2.5 Coder 14B?

Apple M2 Pro (32GB) × Qwen2.5 Coder 14B8K context
YesRuns fully on the GPU
Memory at Q8_017.9 GB of 21.4 GB
Weights 15.7 GBKV cache 1.6 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Speed~8tokens per second
Max context25Ktokens that fit at Q8_0
  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 M2 Pro (32GB) can run Qwen2.5 Coder 14B fully in unified memory at Q8_0 (near-lossless), using about 17.9 GB of the 21.4 GB available, at roughly 8 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Qwen2.5 Coder 14B:

ollama run qwen2.5-coder:14b

Ollama's default download is Q4_K_M (about 11.2 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the Apple M2 Pro (32GB)

Run it in the cloud

No Apple M2 Pro (32GB)? Run Qwen2.5 Coder 14B 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 21.4 GB the Apple M2 Pro (32GB) can use. macOS lets the GPU use about 21.4 GB of the 32 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality31.8 GBToo big—
Q8_0Near-lossless17.9 GBFits~8 tok/s
Q6_KExcellent14.3 GBFits~10 tok/s
Q5_K_MVery good12.7 GBFits~11 tok/s
Q4_K_MGood, most popular11.2 GBFits~13 tok/s
Q3_K_MNoticeably degraded9.4 GBFits~17 tok/s
Q2_KHeavily degraded7.8 GBFits~22 tok/s

Measured speed from real Apple M2 Pro (32GB) owners

Tokens per second that people measured on their own Apple M2 Pro (32GB), next to our estimate.

No one has measured Qwen2.5 Coder 14B on the Apple M2 Pro (32GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M2 Pro (32GB)? Add your real speed

One command times Qwen2.5 Coder 14B 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 -- qwen2.5-coder:14b

Windows (PowerShell)

$env:GPUFIT_MODEL="qwen2.5-coder:14b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Qwen2.5 Coder 14B comfortably

Models that run well on the Apple M2 Pro (32GB)

Frequently asked questions

Can Apple M2 Pro (32GB) run Qwen2.5 Coder 14B?

Yes. The Apple M2 Pro (32GB) can run Qwen2.5 Coder 14B fully in unified memory at Q8_0 (near-lossless), using about 17.9 GB of the 21.4 GB available, at roughly 8 tokens/second.

How much VRAM does Qwen2.5 Coder 14B need?

About 11.2 GB at Q4_K_M with 8,192 tokens of context, and about 31.8 GB at full FP16 precision.

How fast is Qwen2.5 Coder 14B on the Apple M2 Pro (32GB)?

Roughly 8 tokens per second at Q8_0, estimated from the Apple M2 Pro (32GB)'s 200 GB/s memory bandwidth.