Will It Run AI

Can DeepSeek R1 Distill Qwen 14B run on Mac Studio M3 Ultra 256GB?

YES — Runs Great

C45Usable
Estimated from fit model

DeepSeek R1 Distill Qwen 14B needs ~38.7 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~65 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) — 38.7 GB, 65.2 tok/s, Runs well
38.7 GB required184.3 GB available
21% VRAM used

Fit status

Runs well

Decode

65.2 tok/s

TTFT

2969 ms

Safe context

1.4M

Memory

38.7 GB / 184.3 GB

Memory breakdown

Weights8.5 GB
KV Cache1.6 GB
Runtime0.9 GB
Headroom27.6 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill Qwen 14B on Mac Studio M3 Ultra 256GB
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: 65.2 tok/s decode · 3.0s TTFT (warm) · 163 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
ChatCRuns well65.2 tok/s1619 ms1.4M
CodingCRuns well65.2 tok/s2969 ms1.4M
Agentic CodingCRuns well65.2 tok/s4318 ms1.4M
ReasoningCRuns well65.2 tok/s3508 ms1.4M
RAGCRuns well65.2 tok/s5398 ms1.4M

Quantization options

How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowD37
Q3_K_S
3
6.9 GB
LowD37
NVFP4
4
7.8 GB
MediumD37
Q4_K_M
4
8.5 GB
MediumD37
Q5_K_M
5
10.1 GB
HighD37
Q6_K
6
11.5 GB
HighD37
Q8_0
8
15.0 GB
Very HighD37
F16Best for your GPU
16
28.7 GB
MaximumD39

Get started

Copy-paste commands to run DeepSeek R1 Distill Qwen 14B on your machine.

Run

lms load hf-unsloth--deepseek-r1-distill-qwen-14b-gguf && lms server start

Frequently asked questions

Can Mac Studio M3 Ultra 256GB run DeepSeek R1 Distill Qwen 14B?

Yes, Mac Studio M3 Ultra 256GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 65.2 tok/s.

How much VRAM does DeepSeek R1 Distill Qwen 14B need?

DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 38.7 GB of memory with Q4_K_M quantization.

What is the best quantization for DeepSeek R1 Distill Qwen 14B?

The recommended quantization for DeepSeek R1 Distill Qwen 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will DeepSeek R1 Distill Qwen 14B run at on Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, DeepSeek R1 Distill Qwen 14B achieves approximately 65.2 tokens per second decode speed with a time-to-first-token of 2969ms using Q4_K_M quantization.

Can Mac Studio M3 Ultra 256GB run DeepSeek R1 Distill Qwen 14B for coding?

For coding workloads, DeepSeek R1 Distill Qwen 14B on Mac Studio M3 Ultra 256GB receives a C grade with 65.2 tok/s and 1.4M context.

What context window can DeepSeek R1 Distill Qwen 14B use on Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, DeepSeek R1 Distill Qwen 14B can safely use up to 1.4M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

Is unified memory on Mac Studio M3 Ultra 256GB as fast as VRAM for DeepSeek R1 Distill Qwen 14B?

Not always. Mac Studio M3 Ultra 256GB 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 M3 Ultra 256GBSee all hardware for DeepSeek R1 Distill Qwen 14B
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