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URL: https://willitrunai.com/can-run/deepseek-r1-distill-8b-on-m4-mini-32gb


Can DeepSeek R1 Distill 8B run on Mac mini M4 32GB?

YES — Runs Great

B64Good
Estimated — low-sample bucket· few comparable runs

DeepSeek R1 Distill 8B needs ~11.2 GB VRAM. Mac mini M4 32GB has 23.0 GB. With Q4_K_M quantization, expect ~18 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
Share:

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) — 11.2 GB, 17.5 tok/s, Runs well
11.2 GB required23.0 GB available
49% VRAM used

Fit status

Runs well

Decode

17.5 tok/s

TTFT

11056 ms

Safe context

33K

Memory

11.2 GB / 23.0 GB

Memory breakdown

Weights4.9 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom3.5 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 8B on Mac mini M4 32GB
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: 17.5 tok/s decode · 11.1s TTFT (warm) · 44 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
ChatBRuns well17.7 tok/s5964 ms33K
CodingBRuns well17.7 tok/s10935 ms33K
Agentic CodingBRuns well17.7 tok/s15905 ms33K
ReasoningBRuns well17.7 tok/s12923 ms33K
RAGBRuns well17.7 tok/s19881 ms33K

Quantization options

How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on Mac mini M4 32GB (23.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowB61
Q3_K_S
3
3.9 GB
LowB62
NVFP4
4

Get started

Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.

Run

ollama run deepseek-r1:8b

Upgrade options

Hardware that runs DeepSeek R1 Distill 8B well

MacBook Pro M3 Pro 36GBBudget pick
36 GB Unified (+4)150 GB/s (+30)
B
Raises estimated decode speed by about 38%.24.1 tok/s decode

Raises estimated decode speed by about 38%.

~$1,999 MSRP

MacBook Pro M4 Max 36GBBest value
36 GB Unified (+4)410 GB/s (+290)
B
Raises estimated decode speed by about 254%.62 tok/s decode

Raises estimated decode speed by about 254%.

~$2,499 MSRP

Mac Studio M2 Ultra 64GBApple upgrade
64 GB Unified (+32)800 GB/s (+680)
B
Raises estimated decode speed by about 484%.102.2 tok/s decode

Raises estimated decode speed by about 484%.

Adds memory headroom for longer context windows and future model growth.

~$3,999 MSRP

Frequently asked questions

See all results for Mac mini M4 32GBSee all hardware for DeepSeek R1 Distill 8B
4.5 GB
Medium
B62
Q4_K_M
4
4.9 GB
MediumB62
Q5_K_M
5
5.8 GB
HighB63
Q6_K
6
6.6 GB
HighB63
Q8_0
8
8.6 GB
Very HighB65
F16Best for your GPU
16
16.4 GB
MaximumB66

Not always. Mac mini M4 32GB 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.