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Can the Apple M3 Pro (36GB) run Nemotron 3 Nano 30B-A3B?

Apple M3 Pro (36GB) × Nemotron 3 Nano 30B-A3B8K context
YesRuns fully on the GPU
Memory at Q5_K_M23.1 GB of 24.1 GB
Weights 22.5 GBKV cache 0.1 GBRuntime 0.6 GB
QuantQ5_K_MVery good
Speed~36tokens per second
Max context165Ktokens that fit at Q5_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

Yes. The Apple M3 Pro (36GB) can run Nemotron 3 Nano 30B-A3B fully in unified memory at Q5_K_M (very good), using about 23.1 GB of the 24.1 GB available, at roughly 36 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Nemotron 3 Nano 30B-A3B:

ollama run nemotron-3-nano:30b

Ollama's default download is Q4_K_M (about 19.8 GB here). You have room for Q5_K_M, which is very good: 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 Nemotron 3 Nano 30B-A3B 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 quality63.9 GBToo big—
Q8_0Near-lossless34.2 GBToo big—
Q6_KExcellent26.6 GBToo big—
Q5_K_MVery good23.1 GBFits~36 tok/s
Q4_K_MGood, most popular19.8 GBFits~42 tok/s
Q3_K_MNoticeably degraded16.1 GBFits~53 tok/s
Q2_KHeavily degraded12.5 GBFits~69 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 Nemotron 3 Nano 30B-A3B 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 Nemotron 3 Nano 30B-A3B 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 -- nemotron-3-nano:30b

Windows (PowerShell)

$env:GPUFIT_MODEL="nemotron-3-nano:30b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Nemotron 3 Nano 30B-A3B comfortably

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

Frequently asked questions

Can Apple M3 Pro (36GB) run Nemotron 3 Nano 30B-A3B?

Yes. The Apple M3 Pro (36GB) can run Nemotron 3 Nano 30B-A3B fully in unified memory at Q5_K_M (very good), using about 23.1 GB of the 24.1 GB available, at roughly 36 tokens/second.

How much VRAM does Nemotron 3 Nano 30B-A3B need?

About 19.8 GB at Q4_K_M with 8,192 tokens of context, and about 63.9 GB at full FP16 precision.

How fast is Nemotron 3 Nano 30B-A3B on the Apple M3 Pro (36GB)?

Roughly 36 tokens per second at Q5_K_M, estimated from the Apple M3 Pro (36GB)'s 150 GB/s memory bandwidth.