Is unified memory on MacBook Pro M4 Max 64GB as fast as VRAM for Qwen 2.5 Coder 14B?

Not always. MacBook Pro M4 Max 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.

Can Qwen 2.5 Coder 14B run on MacBook Pro M4 Max 64GB?

YES — Runs Great

B62Good

Estimated from fit model

Qwen 2.5 Coder 14B needs ~19.3 GB VRAM. MacBook Pro M4 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~40 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) — 19.3 GB, 38.3 tok/s, Runs well

19.3 GB required46.1 GB available

42% VRAM used

Fit status

Runs well

Decode

38.3 tok/s

TTFT

5057 ms

Safe context

131K

Memory

19.3 GB / 46.1 GB

Memory breakdown

Weights8.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom6.9 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 14B on MacBook Pro M4 Max 64GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers))  # [1, 1, 2, 3, 6, 8, 10]

The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
    """Sort a list using the quicksort algorithm.

    Args:
        arr: List of integers to sort.

    Returns:
        A new sorted list.
    """
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 38.3 tok/s decode · 5.1s TTFT (warm) · 96 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	B	Runs well	38.3 tok/s	2759 ms	131K
Coding	B	Runs well	40.3 tok/s	4807 ms	131K
Agentic Coding	B	Runs well	38.3 tok/s	7356 ms	131K
Reasoning	B	Runs well	38.3 tok/s	5977 ms	131K
RAG	B	Runs well	38.3 tok/s	9195 ms	131K

Quantization options

How Qwen 2.5 Coder 14B (14B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	B56
Q3_K_S	3	6.9 GB	Low	B57
NVFP4	4

Get started

Copy-paste commands to run Qwen 2.5 Coder 14B on your machine.

Run

ollama run qwen2.5-coder:14b

Upgrade options

Hardware that runs Qwen 2.5 Coder 14B well

Mac Studio M3 Ultra 96GBBudget pick

96 GB Unified (+32)819 GB/s (+273)

Raises estimated decode speed by about 84%.70.4 tok/s decode

Raises estimated decode speed by about 84%.

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

~$3,999 MSRP

Radeon Pro W7900 48GBBest value

864 GB/s (+318)

Raises estimated decode speed by about 68%.64.5 tok/s decode

Raises estimated decode speed by about 68%.

~$3,999 MSRP

Frequently asked questions

Can MacBook Pro M4 Max 64GB run Qwen 2.5 Coder 14B?

Yes, MacBook Pro M4 Max 64GB can run Qwen 2.5 Coder 14B with a B grade (Runs well). Expected decode speed: 40.3 tok/s.

How much VRAM does Qwen 2.5 Coder 14B need?

Qwen 2.5 Coder 14B (14B parameters) requires approximately 19.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 14B?

The recommended quantization for Qwen 2.5 Coder 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 14B run at on MacBook Pro M4 Max 64GB?

On MacBook Pro M4 Max 64GB, Qwen 2.5 Coder 14B achieves approximately 40.3 tokens per second decode speed with a time-to-first-token of 4807ms using Q4_K_M quantization.

Can MacBook Pro M4 Max 64GB run Qwen 2.5 Coder 14B for coding?

For coding workloads, Qwen 2.5 Coder 14B on MacBook Pro M4 Max 64GB receives a B grade with 40.3 tok/s and 131K context.

What context window can Qwen 2.5 Coder 14B use on MacBook Pro M4 Max 64GB?

On MacBook Pro M4 Max 64GB, Qwen 2.5 Coder 14B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for MacBook Pro M4 Max 64GB See all hardware for Qwen 2.5 Coder 14B

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<iframe src="https://willitrunai.com/embed/qwen-2.5-coder-14b-on-m4-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

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