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URL: https://willitrunai.com/can-run/nous-hermes-1.0-on-m2-pro-32gb

⇱ Nous Hermes 1.0 on MacBook Pro M2 Pro 32GB? YES


Can Nous Hermes 1.0 run on MacBook Pro M2 Pro 32GB?

YES — With Offload

A70Great
Estimated from fit model

Nous Hermes 1.0 needs ~22.1 GB VRAM. MacBook Pro M2 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: llama.cppCapacity: OffloadBandwidth: 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) — 22.1 GB, 25.5 tok/s, Runs with offload
22.1 GB required23.0 GB available
96% VRAM used

Fit status

Runs with offload

Decode

25.5 tok/s

TTFT

7592 ms

Safe context

16K

Memory

22.1 GB / 23.0 GB

Memory breakdown

Weights5.5 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom3.5 GB

See how fast it feels

See how fast it feelsNous Hermes 1.0 on MacBook Pro M2 Pro 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: 25.5 tok/s decode · 7.6s TTFT (warm) · 64 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

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

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well25.5 tok/s4141 ms16K
CodingARuns with offload25.5 tok/s7592 ms16K
Agentic CodingFToo heavy15.1 tok/s18698 ms16K
ReasoningARuns with offload25.5 tok/s8972 ms16K
RAGFToo heavy15.1 tok/s23373 ms16K

Quantization options

How Nous Hermes 1.0 (9B params) fits at each quantization level on MacBook Pro M2 Pro 32GB (23.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.5 GB
LowB66
Q3_K_S
3
4.4 GB
LowB66
NVFP4
4
5.0 GB
MediumB66
Q4_K_M
4
5.5 GB
MediumB67
Q5_K_M
5
6.5 GB
HighB67
Q6_K
6
7.4 GB
HighB68
Q8_0
8
9.6 GB
Very HighB69
F16Best for your GPU
16
18.5 GB
MaximumA70

Get started

Copy-paste commands to run Nous Hermes 1.0 on your machine.

Run

lms load Nous-Hermes-1.0 && lms server start

Your hardware

More models your MacBook Pro M2 Pro 32GB can run

ModelParamsGradeDecodeCapabilities
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BA19 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS8.5 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS7 tok/s
👁 Alibaba
Qwen3-VL 30B A3B Instruct
30BS20.1 tok/s
👁 Alibaba
Qwen 3.5 35B A3B
35BA16.6 tok/s

Frequently asked questions

See all results for MacBook Pro M2 Pro 32GBSee all hardware for Nous Hermes 1.0