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Can the Apple M2 Ultra (192GB) run Llama 4 Scout 17B-16E?

Apple M2 Ultra (192GB) × Llama 4 Scout 17B-16E8K context
YesRuns fully on the GPU
Memory at Q8_0118 GB of 144 GB
Weights 115.8 GBKV cache 1.6 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Memory118 GBof 144 GB usable
Speed~27tokens per second
  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 Ultra (192GB) can run Llama 4 Scout 17B-16E fully in unified memory at Q8_0 (near-lossless), using about 118 GB of the 144 GB available, at roughly 27 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Llama 4 Scout 17B-16E:

ollama run llama4:scout

Ollama's default download is Q4_K_M (about 68.3 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 Ultra (192GB)

Run it in the cloud

No Apple M2 Ultra (192GB)? Run Llama 4 Scout 17B-16E 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 144 GB the Apple M2 Ultra (192GB) can use. macOS lets the GPU use about 144 GB of the 192 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality220.2 GBToo big—
Q8_0Near-lossless118 GBFits~27 tok/s
Q6_KExcellent91.6 GBFits~34 tok/s
Q5_K_MVery good79.7 GBFits~40 tok/s
Q4_K_MGood, most popular68.3 GBFits~47 tok/s
Q3_K_MNoticeably degraded55.5 GBFits~58 tok/s
Q2_KHeavily degraded43.1 GBFits~75 tok/s

Measured speed from real Apple M2 Ultra (192GB) owners

Tokens per second that people measured on their own Apple M2 Ultra (192GB), next to our estimate.

No one has measured Llama 4 Scout 17B-16E on the Apple M2 Ultra (192GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M2 Ultra (192GB)? Add your real speed

One command times Llama 4 Scout 17B-16E 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 -- llama4:scout

Windows (PowerShell)

$env:GPUFIT_MODEL="llama4:scout"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Llama 4 Scout 17B-16E comfortably

Models that run well on the Apple M2 Ultra (192GB)

Frequently asked questions

Can Apple M2 Ultra (192GB) run Llama 4 Scout 17B-16E?

Yes. The Apple M2 Ultra (192GB) can run Llama 4 Scout 17B-16E fully in unified memory at Q8_0 (near-lossless), using about 118 GB of the 144 GB available, at roughly 27 tokens/second.

How much VRAM does Llama 4 Scout 17B-16E need?

About 68.3 GB at Q4_K_M with 8,192 tokens of context, and about 220.2 GB at full FP16 precision.

How fast is Llama 4 Scout 17B-16E on the Apple M2 Ultra (192GB)?

Roughly 27 tokens per second at Q8_0, estimated from the Apple M2 Ultra (192GB)'s 800 GB/s memory bandwidth.