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Can the Apple M5 (16GB) run Phi-4 Mini 3.8B?

Apple M5 (16GB) × Phi-4 Mini 3.8B8K context
YesRuns fully on the GPU
Memory at FP169.4 GB of 10.7 GB
Weights 7.7 GBKV cache 1.1 GBRuntime 0.6 GB
QuantFP16Full quality
Speed~12tokens per second
Max context17Ktokens that fit at FP16
  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 M5 (16GB) can run Phi-4 Mini 3.8B fully in unified memory at FP16 (full quality), using about 9.4 GB of the 10.7 GB available, at roughly 12 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Phi-4 Mini 3.8B:

ollama run phi4-mini:3.8b

Ollama's default download is Q4_K_M (about 4 GB here). You have room for FP16, which is full quality: pick that GGUF in LM Studio or from Hugging Face.

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

Run it in the cloud

No Apple M5 (16GB)? Run Phi-4 Mini 3.8B 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 M5 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality9.4 GBFits~12 tok/s
Q8_0Near-lossless5.8 GBFits~23 tok/s
Q6_KExcellent4.8 GBFits~29 tok/s
Q5_K_MVery good4.4 GBFits~34 tok/s
Q4_K_MGood, most popular4 GBFits~39 tok/s
Q3_K_MNoticeably degraded3.6 GBFits~49 tok/s
Q2_KHeavily degraded3.1 GBFits~64 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 Mini 3.8B 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 Mini 3.8B 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-mini:3.8b

Windows (PowerShell)

$env:GPUFIT_MODEL="phi4-mini:3.8b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Phi-4 Mini 3.8B comfortably

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

Frequently asked questions

Can Apple M5 (16GB) run Phi-4 Mini 3.8B?

Yes. The Apple M5 (16GB) can run Phi-4 Mini 3.8B fully in unified memory at FP16 (full quality), using about 9.4 GB of the 10.7 GB available, at roughly 12 tokens/second.

How much VRAM does Phi-4 Mini 3.8B need?

About 4 GB at Q4_K_M with 8,192 tokens of context, and about 9.4 GB at full FP16 precision.

How fast is Phi-4 Mini 3.8B on the Apple M5 (16GB)?

Roughly 12 tokens per second at FP16, estimated from the Apple M5 (16GB)'s 153 GB/s memory bandwidth.