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Can the Apple M5 (16GB) run Phi-4 Reasoning 14B?

Apple M5 (16GB) × Phi-4 Reasoning 14B8K context
Yes, with heavy quantizationFits only at a low-quality quant
Memory at Q3_K_M9.5 GB of 10.7 GB
Weights 7.2 GBKV cache 1.7 GBRuntime 0.6 GB
QuantQ3_K_MNoticeably degraded
Speed~13tokens per second
Max context13Ktokens that fit at Q3_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

Only just. Phi-4 Reasoning 14B fits on the Apple M5 (16GB) at Q3_K_M, which costs noticeable quality. Expect about 13 tokens/second. A card with more memory is a better experience.

Try other context lengths

Run it with Ollama

Ollama's default phi4-reasoning:14b download is Q4_K_M, which needs about 11.2 GB, more than the 10.7 GB available. Download the Q3_K_M GGUF instead (LM Studio lists quants per model), or try a smaller context length.

New to this? Step-by-step setup for the Apple M5 (16GB)

Run it in the cloud

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 10.7 GB the Apple M5 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality31.7 GBToo big—
Q8_0Near-lossless17.9 GBToo big—
Q6_KExcellent14.3 GBToo big—
Q5_K_MVery good12.7 GBToo big—
Q4_K_MGood, most popular11.2 GBToo big—
Q3_K_MNoticeably degraded9.5 GBFits~13 tok/s
Q2_KHeavily degraded7.8 GBFits~17 tok/s

Measured speed from real Apple M5 (16GB) owners

Tokens per second that people measured on their own Apple M5 (16GB), next to our estimate.

No one has measured Phi-4 Reasoning 14B on the Apple M5 (16GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M5 (16GB)? Add your real speed

One command times Phi-4 Reasoning 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 -- phi4-reasoning:14b

Windows (PowerShell)

$env:GPUFIT_MODEL="phi4-reasoning:14b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Phi-4 Reasoning 14B comfortably

Check RTX 3060 12GB prices

Models that run well on the Apple M5 (16GB)

Frequently asked questions

Can Apple M5 (16GB) run Phi-4 Reasoning 14B?

Only just. Phi-4 Reasoning 14B fits on the Apple M5 (16GB) at Q3_K_M, which costs noticeable quality. Expect about 13 tokens/second. A card with more memory is a better experience.

How much VRAM does Phi-4 Reasoning 14B need?

About 11.2 GB at Q4_K_M with 8,192 tokens of context, and about 31.7 GB at full FP16 precision.

How fast is Phi-4 Reasoning 14B on the Apple M5 (16GB)?

Roughly 13 tokens per second at Q3_K_M, estimated from the Apple M5 (16GB)'s 153 GB/s memory bandwidth.