Rent a GPU

Can the Apple M4 Pro (48GB) run DeepSeek R1 Distill Llama 70B?

Apple M4 Pro (48GB) × DeepSeek R1 Distill Llama 70B8K context
Yes, with heavy quantizationFits only at a low-quality quant
Memory at Q2_K29.8 GB of 36 GB
Weights 26.5 GBKV cache 2.7 GBRuntime 0.6 GB
QuantQ2_KHeavily degraded
Speed~6tokens per second
Max context25Ktokens that fit at Q2_K
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Only just. DeepSeek R1 Distill Llama 70B fits on the Apple M4 Pro (48GB) at Q2_K, which costs noticeable quality. Expect about 6 tokens/second. A card with more memory is a better experience.

Try other context lengths

Run it with Ollama

Ollama's default deepseek-r1:70b download is Q4_K_M, which needs about 46.1 GB, more than the 36 GB available. Download the Q2_K GGUF instead (LM Studio lists quants per model), or try a smaller context length.

New to this? Step-by-step setup for the Apple M4 Pro (48GB)

Run it in the cloud

Want full quality? Run DeepSeek R1 Distill Llama 70B on a bigger rented GPU.

Rent a cloud GPU by the hour. No upfront cost, stop any time. Not sure whether to rent or buy? Compare the cost.

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 36 GB the Apple M4 Pro (48GB) can use. macOS lets the GPU use about 36 GB of the 48 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality144.5 GBToo big—
Q8_0Near-lossless78.3 GBToo big—
Q6_KExcellent61.2 GBToo big—
Q5_K_MVery good53.5 GBToo big—
Q4_K_MGood, most popular46.1 GBToo big—
Q3_K_MNoticeably degraded37.8 GBToo big—
Q2_KHeavily degraded29.8 GBFits~6 tok/s

Measured speed from real Apple M4 Pro (48GB) owners

Tokens per second that people measured on their own Apple M4 Pro (48GB), next to our estimate.

No one has measured DeepSeek R1 Distill Llama 70B on the Apple M4 Pro (48GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M4 Pro (48GB)? Add your real speed

One command times DeepSeek R1 Distill Llama 70B 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 -- deepseek-r1:70b

Windows (PowerShell)

$env:GPUFIT_MODEL="deepseek-r1:70b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run DeepSeek R1 Distill Llama 70B comfortably

Check Mac Studio M4 Max (64 GB) prices

Models that run well on the Apple M4 Pro (48GB)

Frequently asked questions

Can Apple M4 Pro (48GB) run DeepSeek R1 Distill Llama 70B?

Only just. DeepSeek R1 Distill Llama 70B fits on the Apple M4 Pro (48GB) at Q2_K, which costs noticeable quality. Expect about 6 tokens/second. A card with more memory is a better experience.

How much VRAM does DeepSeek R1 Distill Llama 70B need?

About 46.1 GB at Q4_K_M with 8,192 tokens of context, and about 144.5 GB at full FP16 precision.

How fast is DeepSeek R1 Distill Llama 70B on the Apple M4 Pro (48GB)?

Roughly 6 tokens per second at Q2_K, estimated from the Apple M4 Pro (48GB)'s 273 GB/s memory bandwidth.