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Can the Apple M3 Pro (36GB) run Phi-3.5 Mini 3.8B?

Apple M3 Pro (36GB) × Phi-3.5 Mini 3.8B8K context
YesRuns fully on the GPU
Memory at FP1611.5 GB of 24.1 GB
Weights 7.6 GBKV cache 3.2 GBRuntime 0.6 GB
QuantFP16Full quality
Speed~12tokens per second
Max context38Ktokens 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 M3 Pro (36GB) can run Phi-3.5 Mini 3.8B fully in unified memory at FP16 (full quality), using about 11.5 GB of the 24.1 GB available, at roughly 12 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Phi-3.5 Mini 3.8B:

ollama run phi3.5:3.8b

Ollama's default download is Q4_K_M (about 6.1 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 M3 Pro (36GB)

Run it in the cloud

No Apple M3 Pro (36GB)? Run Phi-3.5 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 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 quality11.5 GBFits~12 tok/s
Q8_0Near-lossless7.9 GBFits~22 tok/s
Q6_KExcellent7 GBFits~29 tok/s
Q5_K_MVery good6.5 GBFits~33 tok/s
Q4_K_MGood, most popular6.1 GBFits~39 tok/s
Q3_K_MNoticeably degraded5.7 GBFits~48 tok/s
Q2_KHeavily degraded5.3 GBFits~63 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 Phi-3.5 Mini 3.8B 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 Phi-3.5 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 -- phi3.5:3.8b

Windows (PowerShell)

$env:GPUFIT_MODEL="phi3.5:3.8b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Phi-3.5 Mini 3.8B comfortably

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

Frequently asked questions

Can Apple M3 Pro (36GB) run Phi-3.5 Mini 3.8B?

Yes. The Apple M3 Pro (36GB) can run Phi-3.5 Mini 3.8B fully in unified memory at FP16 (full quality), using about 11.5 GB of the 24.1 GB available, at roughly 12 tokens/second.

How much VRAM does Phi-3.5 Mini 3.8B need?

About 6.1 GB at Q4_K_M with 8,192 tokens of context, and about 11.5 GB at full FP16 precision.

How fast is Phi-3.5 Mini 3.8B on the Apple M3 Pro (36GB)?

Roughly 12 tokens per second at FP16, estimated from the Apple M3 Pro (36GB)'s 150 GB/s memory bandwidth.