Will It Run AI

Can DeepSeek R1 Distill 32B run on Mac Studio M1 Ultra 64GB?

YES — Runs Great

A77Great
Estimated from fit model

DeepSeek R1 Distill 32B needs ~31.2 GB VRAM. Mac Studio M1 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~24 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
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Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 31.2 GB, 24.3 tok/s, Runs well
31.2 GB required46.1 GB available
68% VRAM used

Fit status

Runs well

Decode

24.3 tok/s

TTFT

7953 ms

Safe context

33K

Memory

31.2 GB / 46.1 GB

Memory breakdown

Weights19.5 GB
KV Cache3.9 GB
Runtime0.9 GB
Headroom6.9 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 32B on Mac Studio M1 Ultra 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 24.3 tok/s decode · 8.0s TTFT (warm) · 61 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Shared-memory contention still exists

The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well24.3 tok/s4338 ms33K
CodingARuns well24.3 tok/s7953 ms33K
Agentic CodingARuns well24.3 tok/s11567 ms33K
ReasoningARuns well24.3 tok/s9399 ms33K
RAGARuns well24.3 tok/s14459 ms33K

Quantization options

How DeepSeek R1 Distill 32B (32B params) fits at each quantization level on Mac Studio M1 Ultra 64GB (46.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
12.5 GB
LowB69
Q3_K_S
3
15.7 GB
LowA71
NVFP4
4
17.9 GB
MediumA71
Q4_K_M
4
19.5 GB
MediumA72
Q5_K_M
5
23.0 GB
HighA73
Q6_K
6
26.2 GB
HighA74
Q8_0Best for your GPU
8
34.2 GB
Very HighA73
F16
16
65.6 GB
MaximumF0

Get started

Copy-paste commands to run DeepSeek R1 Distill 32B on your machine.

Run

ollama run deepseek-r1:32b

Your hardware

More models your Mac Studio M1 Ultra 64GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3.6 35B A3B35BS55.9 tok/s
AlibabaQwen 3.5 35B A3B35BS60.8 tok/s
Moonshot AIKimi Linear 48B A3B48BA15 tok/s
IBMGranite Code 34B34BA23 tok/s
CohereCommand R 35B35BA22.4 tok/s

Frequently asked questions

Can Mac Studio M1 Ultra 64GB run DeepSeek R1 Distill 32B?

Yes, Mac Studio M1 Ultra 64GB can run DeepSeek R1 Distill 32B with a A grade (Runs well). Expected decode speed: 24.3 tok/s.

How much VRAM does DeepSeek R1 Distill 32B need?

DeepSeek R1 Distill 32B (32B parameters) requires approximately 31.2 GB of memory with Q4_K_M quantization.

What is the best quantization for DeepSeek R1 Distill 32B?

The recommended quantization for DeepSeek R1 Distill 32B is Q4_K_M, which balances quality and memory efficiency.

What speed will DeepSeek R1 Distill 32B run at on Mac Studio M1 Ultra 64GB?

On Mac Studio M1 Ultra 64GB, DeepSeek R1 Distill 32B achieves approximately 24.3 tokens per second decode speed with a time-to-first-token of 7953ms using Q4_K_M quantization.

Can Mac Studio M1 Ultra 64GB run DeepSeek R1 Distill 32B for coding?

For coding workloads, DeepSeek R1 Distill 32B on Mac Studio M1 Ultra 64GB receives a A grade with 24.3 tok/s and 33K context.

What context window can DeepSeek R1 Distill 32B use on Mac Studio M1 Ultra 64GB?

On Mac Studio M1 Ultra 64GB, DeepSeek R1 Distill 32B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

Is unified memory on Mac Studio M1 Ultra 64GB as fast as VRAM for DeepSeek R1 Distill 32B?

Not always. Mac Studio M1 Ultra 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.

See all results for Mac Studio M1 Ultra 64GBSee all hardware for DeepSeek R1 Distill 32B
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