Will It Run AI

Can Yi 1.5 9B Chat run on MacBook Pro M4 Pro 48GB?

YES — Runs Great

C46Usable
Estimated — low-sample bucket· few comparable runs

Yi 1.5 9B Chat needs ~12.6 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~35 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: 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) 12.6 GB, 35.2 tok/s, Runs well
12.6 GB required34.6 GB available
36% VRAM used

Fit status

Runs well

Decode

35.2 tok/s

TTFT

5496 ms

Safe context

349K

Memory

12.6 GB / 34.6 GB

Memory breakdown

Weights5.5 GB
KV Cache1.1 GB
Runtime0.9 GB
Headroom5.2 GB

See how fast it feels

See how fast it feelsYi 1.5 9B Chat on MacBook Pro M4 Pro 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: 35.2 tok/s decode · 5.5s TTFT (warm) · 88 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 well35.2 tok/s2998 ms349K
CodingCRuns well35.2 tok/s5496 ms349K
Agentic CodingCRuns well35.2 tok/s7994 ms349K
ReasoningCRuns well35.2 tok/s6495 ms349K
RAGCRuns well35.2 tok/s9992 ms349K

Quantization options

How Yi 1.5 9B Chat (9B params) fits at each quantization level on MacBook Pro M4 Pro 48GB (34.6 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.5 GB
LowC43
Q3_K_S
3
4.4 GB
LowC43
NVFP4
4
5.0 GB
MediumC43
Q4_K_M
4
5.5 GB
MediumC43
Q5_K_M
5
6.5 GB
HighC44
Q6_K
6
7.4 GB
HighC44
Q8_0
8
9.6 GB
Very HighC45
F16Best for your GPU
16
18.5 GB
MaximumC49

Get started

Copy-paste commands to run Yi 1.5 9B Chat on your machine.

Run

lms load hf-bartowski--yi-1-5-9b-chat-gguf && lms server start

Opciones de mejora

Hardware que ejecuta bien Yi 1.5 9B Chat

Frequently asked questions

Can MacBook Pro M4 Pro 48GB run Yi 1.5 9B Chat?

Yes, MacBook Pro M4 Pro 48GB can run Yi 1.5 9B Chat with a C grade (Runs well). Expected decode speed: 35.2 tok/s.

How much VRAM does Yi 1.5 9B Chat need?

Yi 1.5 9B Chat (9B parameters) requires approximately 12.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Yi 1.5 9B Chat?

The recommended quantization for Yi 1.5 9B Chat is Q4_K_M, which balances quality and memory efficiency.

What speed will Yi 1.5 9B Chat run at on MacBook Pro M4 Pro 48GB?

On MacBook Pro M4 Pro 48GB, Yi 1.5 9B Chat achieves approximately 35.2 tokens per second decode speed with a time-to-first-token of 5496ms using Q4_K_M quantization.

Can MacBook Pro M4 Pro 48GB run Yi 1.5 9B Chat for coding?

For coding workloads, Yi 1.5 9B Chat on MacBook Pro M4 Pro 48GB receives a C grade with 35.2 tok/s and 349K context.

What context window can Yi 1.5 9B Chat use on MacBook Pro M4 Pro 48GB?

On MacBook Pro M4 Pro 48GB, Yi 1.5 9B Chat can safely use up to 349K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M4 Pro 48GB as fast as VRAM for Yi 1.5 9B Chat?

Not always. MacBook Pro M4 Pro 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.

See all results for MacBook Pro M4 Pro 48GBSee all hardware for Yi 1.5 9B Chat
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