Can Qwen3-Coder 480B A35B Instruct run on Mac Studio M3 Ultra 96GB?

NO — Won't Fit

F0Won't run

Estimated from fit model

Qwen3-Coder 480B A35B Instruct needs ~306.9 GB but Mac Studio M3 Ultra 96GB only has 69.1 GB. Try a smaller quantization or lighter model.

Runtime: llama.cppCapacity: No fitBandwidth: HighStack: StandardBottleneck: Memory capacity

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) — 306.9 GB, exceeds 69.1 GB available

306.9 GB required69.1 GB available

444% VRAM needed

237.8 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

4.0 tok/s

TTFT

47809 ms

Safe context

Memory

306.9 GB / 69.1 GB

Offload

80%

Memory breakdown

Weights292.8 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom10.4 GB

See how fast it feels

With memory offload — actual speed may be lower

See how fast it feelsQwen3-Coder 480B A35B Instruct on Mac Studio M3 Ultra 96GB
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: 4.0 tok/s decode · 47.8s TTFT (warm) · 10 tok/s prefill

What limits this setup

Usable shared or unified memory is the main blocker for this model.

Not enough usable memory

The model needs 306.9 GB, but this setup only exposes 69.1 GB of usable shared or unified memory.

Best improvement path

Move to a larger memory pool

A larger unified-memory SKU or a discrete high-bandwidth GPU is the cleanest way to make this model practical.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	F	Too heavy	4.0 tok/s	26078 ms	4K
Coding	F	Too heavy	4.0 tok/s	47809 ms	4K
Agentic Coding	F	Too heavy	4.0 tok/s	69540 ms	4K
Reasoning	F	Too heavy	4.0 tok/s	56501 ms	4K
RAG	F	Too heavy	4.0 tok/s	86925 ms	4K

Quantization options

How Qwen3-Coder 480B A35B Instruct (480B params) fits at each quantization level on Mac Studio M3 Ultra 96GB (69.1 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	187.2 GB	Low	F0
Q3_K_S	3	235.2 GB	Low	F0
NVFP4	4	268.8 GB	Medium	F0
Q4_K_M	4	292.8 GB	Medium	F0
Q5_K_M	5	345.6 GB	High	F0
Q6_K	6	393.6 GB	High	F0
Q8_0	8	513.6 GB	Very High	F0
F16	16	984.0 GB	Maximum	F0

Upgrade options

Hardware that runs Qwen3-Coder 480B A35B Instruct well

AMD Instinct MI350X 288GBBest value

288 GB VRAM (+192)8000 GB/s (+7181)

Makes the model fit on the accelerator instead of staying completely out of reach.35.3 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Raises estimated decode speed by about 782%.

~$8,000 MSRP

Frequently asked questions

Can Mac Studio M3 Ultra 96GB run Qwen3-Coder 480B A35B Instruct?

No, Qwen3-Coder 480B A35B Instruct requires more memory than Mac Studio M3 Ultra 96GB provides.

How much VRAM does Qwen3-Coder 480B A35B Instruct need?

Qwen3-Coder 480B A35B Instruct (480B parameters) requires approximately 306.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-Coder 480B A35B Instruct?

The recommended quantization for Qwen3-Coder 480B A35B Instruct is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen3-Coder 480B A35B Instruct run at on Mac Studio M3 Ultra 96GB?

On Mac Studio M3 Ultra 96GB, Qwen3-Coder 480B A35B Instruct achieves approximately 4.0 tokens per second decode speed with a time-to-first-token of 47809ms using Q4_K_M quantization.

Can Mac Studio M3 Ultra 96GB run Qwen3-Coder 480B A35B Instruct for coding?

For coding workloads, Qwen3-Coder 480B A35B Instruct on Mac Studio M3 Ultra 96GB receives a F grade with 4.0 tok/s and 4K context.

What context window can Qwen3-Coder 480B A35B Instruct use on Mac Studio M3 Ultra 96GB?

On Mac Studio M3 Ultra 96GB, Qwen3-Coder 480B A35B Instruct can safely use up to 4K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.

What should I upgrade first if Qwen3-Coder 480B A35B Instruct feels slow on Mac Studio M3 Ultra 96GB?

Move to a larger memory pool. A larger unified-memory SKU or a discrete high-bandwidth GPU is the cleanest way to make this model practical.

Is unified memory on Mac Studio M3 Ultra 96GB as fast as VRAM for Qwen3-Coder 480B A35B Instruct?

Not always. Mac Studio M3 Ultra 96GB 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 Studio M3 Ultra 96GB See all hardware for Qwen3-Coder 480B A35B Instruct

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/qwen-3-coder-480b-a35b-on-m3-ultra-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Too heavy

4.0 tok/s

26078 ms

Coding

Too heavy

4.0 tok/s

47809 ms

Agentic Coding

Too heavy

4.0 tok/s

69540 ms

Reasoning

Too heavy

4.0 tok/s

56501 ms

RAG

Too heavy

4.0 tok/s

86925 ms

Quantization options

How Qwen3-Coder 480B A35B Instruct (480B params) fits at each quantization level on Mac Studio M3 Ultra 96GB (69.1 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	187.2 GB	Low	F0
Q3_K_S	3	235.2 GB	Low	F0
NVFP4	4	268.8 GB	Medium	F0
Q4_K_M	4	292.8 GB	Medium	F0
Q5_K_M	5	345.6 GB	High	F0
Q6_K	6	393.6 GB	High	F0
Q8_0	8	513.6 GB	Very High	F0
F16	16	984.0 GB	Maximum	F0