Will It Run AI

Can Nous Dolphin 13B run on Mac mini M4 64GB?

YES — Runs Great

B69Good
Estimated from fit model

Nous Dolphin 13B needs ~29.7 GB VRAM. Mac mini M4 64GB has 46.1 GB. With Q5_K_M quantization, expect ~8 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: Very lowStack: BasicBottleneck: Memory bandwidth
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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

Q5_K_M (High quality) 29.7 GB, 8.3 tok/s, Runs well
29.7 GB required46.1 GB available
64% VRAM used

Fit status

Runs well

Decode

8.3 tok/s

TTFT

23366 ms

Safe context

16K

Memory

29.7 GB / 46.1 GB

Memory breakdown

Weights9.4 GB
KV Cache12.2 GB
Runtime1.2 GB
Headroom6.9 GB

See how fast it feels

See how fast it feelsNous Dolphin 13B on Mac mini M4 64GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API. When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed. Key benefits of running locally: - Full privacy: your prompts never leave your machine - No per-token cost or rate limits - Works offline once the model is downloaded - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb: Model size Q4 (4-bit) Q8 (8-bit) FP16 7B params ~4.3 GB ~7.5 GB ~14 GB 13B params ~7.9 GB ~13.9 GB ~26 GB 70B params ~42.7 GB ~74.9 GB ~140 GB Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 8.3 tok/s decode · 23.4s TTFT (warm) · 21 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 well8.3 tok/s12745 ms16K
CodingBRuns well8.3 tok/s23366 ms16K
Agentic CodingBTight fit8.3 tok/s33987 ms16K
ReasoningBRuns well8.3 tok/s27614 ms16K
RAGBTight fit8.3 tok/s42484 ms16K

Quantization options

How Nous Dolphin 13B (13B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB63
Q3_K_S
3
6.4 GB
LowB63
NVFP4
4
7.3 GB
MediumB63
Q4_K_M
4
7.9 GB
MediumB63
Q5_K_M
5
9.4 GB
HighB64
Q6_K
6
10.7 GB
HighB64
Q8_0
8
13.9 GB
Very HighB65
F16Best for your GPU
16
26.7 GB
MaximumB69

Get started

Copy-paste commands to run Nous Dolphin 13B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "nousresearch/Nous-Dolphin-13B" \ --hf-file "Nous-Dolphin-13B-Q5_K_M.gguf" \ -c 4096 -ngl 99

Opciones de mejora

Hardware que ejecuta bien Nous Dolphin 13B

Frequently asked questions

Can Mac mini M4 64GB run Nous Dolphin 13B?

Yes, Mac mini M4 64GB can run Nous Dolphin 13B with a B grade (Runs well). Expected decode speed: 8.3 tok/s.

How much VRAM does Nous Dolphin 13B need?

Nous Dolphin 13B (13B parameters) requires approximately 29.7 GB of memory with Q5_K_M quantization.

What is the best quantization for Nous Dolphin 13B?

The recommended quantization for Nous Dolphin 13B is Q5_K_M, which balances quality and memory efficiency.

What speed will Nous Dolphin 13B run at on Mac mini M4 64GB?

On Mac mini M4 64GB, Nous Dolphin 13B achieves approximately 8.3 tokens per second decode speed with a time-to-first-token of 23366ms using Q5_K_M quantization.

Can Mac mini M4 64GB run Nous Dolphin 13B for coding?

For coding workloads, Nous Dolphin 13B on Mac mini M4 64GB receives a B grade with 8.3 tok/s and 16K context.

What context window can Nous Dolphin 13B use on Mac mini M4 64GB?

On Mac mini M4 64GB, Nous Dolphin 13B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.

Is unified memory on Mac mini M4 64GB as fast as VRAM for Nous Dolphin 13B?

Not always. Mac mini M4 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 mini M4 64GBSee all hardware for Nous Dolphin 13B
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