Is unified memory on MacBook Pro M4 Max 48GB as fast as VRAM for NousResearch Hermes 4 14B?

Not always. MacBook Pro M4 Max 48GB 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.

Can NousResearch Hermes 4 14B run on MacBook Pro M4 Max 48GB?

YES — Runs Great

C49Usable

Estimated from fit model

NousResearch Hermes 4 14B needs ~16.3 GB VRAM. MacBook Pro M4 Max 48GB has 34.6 GB. With Q4_K_M quantization, expect ~35 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced

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) — 16.3 GB, 35.4 tok/s, Runs well

16.3 GB required34.6 GB available

47% VRAM used

Fit status

Runs well

Decode

35.4 tok/s

TTFT

5462 ms

Safe context

194K

Memory

16.3 GB / 34.6 GB

Memory breakdown

Weights8.5 GB

KV Cache1.6 GB

Runtime0.9 GB

Headroom5.2 GB

See how fast it feels

See how fast it feelsNousResearch Hermes 4 14B on MacBook Pro M4 Max 48GB
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: 35.4 tok/s decode · 5.5s TTFT (warm) · 89 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Runs well	35.4 tok/s	2979 ms	194K
Coding	C	Runs well	35.4 tok/s	5462 ms	194K
Agentic Coding	C	Runs well	35.4 tok/s	7945 ms	194K
Reasoning	C	Runs well	35.4 tok/s	6455 ms	194K
RAG	C	Runs well	35.4 tok/s	9931 ms	194K

Quantization options

How NousResearch Hermes 4 14B (14B params) fits at each quantization level on MacBook Pro M4 Max 48GB (34.6 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	C43
Q3_K_S	3	6.9 GB	Low	C44
NVFP4	4

Get started

Copy-paste commands to run NousResearch Hermes 4 14B on your machine.

Run

lms load hf-bartowski--nousresearch-hermes-4-14b-gguf && lms server start

Upgrade options

Hardware that runs NousResearch Hermes 4 14B well

RTX PRO 5000 Blackwell 48GBBudget pick

1344 GB/s (+798)

Raises estimated decode speed by about 273%.132.2 tok/s decode

Raises estimated decode speed by about 273%.

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

~$4,999 MSRP

RTX 6000 Ada 48GBBest value

960 GB/s (+414)

Raises estimated decode speed by about 160%.92.2 tok/s decode

Raises estimated decode speed by about 160%.

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

~$6,800 MSRP

Frequently asked questions

Can MacBook Pro M4 Max 48GB run NousResearch Hermes 4 14B?

Yes, MacBook Pro M4 Max 48GB can run NousResearch Hermes 4 14B with a C grade (Runs well). Expected decode speed: 35.4 tok/s.

How much VRAM does NousResearch Hermes 4 14B need?

NousResearch Hermes 4 14B (14B parameters) requires approximately 16.3 GB of memory with Q4_K_M quantization.

What is the best quantization for NousResearch Hermes 4 14B?

The recommended quantization for NousResearch Hermes 4 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will NousResearch Hermes 4 14B run at on MacBook Pro M4 Max 48GB?

On MacBook Pro M4 Max 48GB, NousResearch Hermes 4 14B achieves approximately 35.4 tokens per second decode speed with a time-to-first-token of 5462ms using Q4_K_M quantization.

Can MacBook Pro M4 Max 48GB run NousResearch Hermes 4 14B for coding?

For coding workloads, NousResearch Hermes 4 14B on MacBook Pro M4 Max 48GB receives a C grade with 35.4 tok/s and 194K context.

What context window can NousResearch Hermes 4 14B use on MacBook Pro M4 Max 48GB?

On MacBook Pro M4 Max 48GB, NousResearch Hermes 4 14B can safely use up to 194K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for MacBook Pro M4 Max 48GB See all hardware for NousResearch Hermes 4 14B

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