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Can the Apple M2 Ultra (192GB) run Qwen3 0.6B?

Apple M2 Ultra (192GB) × Qwen3 0.6B8K context
YesRuns fully on the GPU
Memory at FP163 GB of 144 GB
Weights 1.5 GBKV cache 0.9 GBRuntime 0.6 GB
QuantFP16Full quality
Speed~320tokens per second
Max context32Kthe model's full window
  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 Qwen3 0.6B fully in unified memory at FP16 (full quality), using about 3 GB of the 144 GB available, at roughly 320 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Qwen3 0.6B:

ollama run qwen3:0.6b

Ollama's default download is Q4_K_M (about 2 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 M2 Ultra (192GB)

Run it in the cloud

No Apple M2 Ultra (192GB)? Run Qwen3 0.6B 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 quality3 GBFits~320 tok/s
Q8_0Near-lossless2.3 GBFits~602 tok/s
Q6_KExcellent2.2 GBFits~780 tok/s
Q5_K_MVery good2.1 GBFits~900 tok/s
Q4_K_MGood, most popular2 GBFits~1056 tok/s
Q3_K_MNoticeably degraded1.9 GBFits~1309 tok/s
Q2_KHeavily degraded1.8 GBFits~1707 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 Qwen3 0.6B 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 Qwen3 0.6B 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 -- qwen3:0.6b

Windows (PowerShell)

$env:GPUFIT_MODEL="qwen3:0.6b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Qwen3 0.6B comfortably

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

Frequently asked questions

Can Apple M2 Ultra (192GB) run Qwen3 0.6B?

Yes. The Apple M2 Ultra (192GB) can run Qwen3 0.6B fully in unified memory at FP16 (full quality), using about 3 GB of the 144 GB available, at roughly 320 tokens/second.

How much VRAM does Qwen3 0.6B need?

About 2 GB at Q4_K_M with 8,192 tokens of context, and about 3 GB at full FP16 precision.

How fast is Qwen3 0.6B on the Apple M2 Ultra (192GB)?

Roughly 320 tokens per second at FP16, estimated from the Apple M2 Ultra (192GB)'s 800 GB/s memory bandwidth.