Can Qwen 3.5 35B A3B run on NVIDIA A40 48GB?

YES — Runs Great

S96Excellent

Estimated from fit model

Qwen 3.5 35B A3B needs ~28.8 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~75 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: 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) — 28.8 GB, 75.0 tok/s, Runs well

28.8 GB required48.0 GB available

60% VRAM used

Fit status

Runs well

Decode

75.0 tok/s

TTFT

2580 ms

Safe context

131K

Memory

28.8 GB / 48.0 GB

Memory breakdown

Weights21.3 GB

KV Cache1.5 GB

Runtime1.2 GB

Headroom4.8 GB

See how fast it feels

See how fast it feelsQwen 3.5 35B A3B on NVIDIA A40 48GB
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: 75.0 tok/s decode · 2.6s TTFT (warm) · 188 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs well	75.0 tok/s	1408 ms	131K
Coding	S	Runs well	75.0 tok/s	2580 ms	131K
Agentic Coding	S	Runs well	75.0 tok/s	3753 ms	131K
Reasoning	S	Runs well	75.0 tok/s	3050 ms	131K
RAG	S	Runs well	75.0 tok/s	4692 ms	131K

Quantization options

How Qwen 3.5 35B A3B (35B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.7 GB	Low	S86
Q3_K_S	3	17.2 GB	Low	S87
NVFP4	4	19.6 GB	Medium	S88
Q4_K_M	4	21.3 GB	Medium	S88
Q5_K_M	5	25.2 GB	High	S90
Q6_K	6	28.7 GB	High	S90
Q8_0Best for your GPU	8	37.5 GB	Very High	S89
F16	16	71.8 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 3.5 35B A3B on your machine.

Run

ollama run qwen3.5:35b-a3b

Frequently asked questions

Can NVIDIA A40 48GB run Qwen 3.5 35B A3B?

Yes, NVIDIA A40 48GB can run Qwen 3.5 35B A3B with a S grade (Runs well). Expected decode speed: 75.0 tok/s.

How much VRAM does Qwen 3.5 35B A3B need?

Qwen 3.5 35B A3B (35B parameters) requires approximately 28.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.5 35B A3B?

The recommended quantization for Qwen 3.5 35B A3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.5 35B A3B run at on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Qwen 3.5 35B A3B achieves approximately 75.0 tokens per second decode speed with a time-to-first-token of 2580ms using Q4_K_M quantization.

Can NVIDIA A40 48GB run Qwen 3.5 35B A3B for coding?

For coding workloads, Qwen 3.5 35B A3B on NVIDIA A40 48GB receives a S grade with 75.0 tok/s and 131K context.

What context window can Qwen 3.5 35B A3B use on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Qwen 3.5 35B A3B 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 NVIDIA A40 48GB See all hardware for Qwen 3.5 35B A3B

Embed this result▼

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<iframe src="https://willitrunai.com/embed/qwen-3.5-35b-a3b-on-a40-48gb" 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

Runs well

75.0 tok/s

1408 ms

131K

Coding

Runs well

75.0 tok/s

2580 ms

131K

Agentic Coding

Runs well

75.0 tok/s

3753 ms

131K

Reasoning

Runs well

75.0 tok/s

3050 ms

131K

RAG

Runs well

75.0 tok/s

4692 ms

131K

Quantization options

How Qwen 3.5 35B A3B (35B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.7 GB	Low	S86
Q3_K_S	3	17.2 GB	Low	S87
NVFP4	4	19.6 GB	Medium	S88
Q4_K_M	4	21.3 GB	Medium	S88
Q5_K_M	5	25.2 GB	High	S90
Q6_K	6	28.7 GB	High	S90
Q8_0Best for your GPU	8	37.5 GB	Very High	S89
F16	16	71.8 GB	Maximum	F0

Frequently asked questions

Can NVIDIA A40 48GB run Qwen 3.5 35B A3B?

Yes, NVIDIA A40 48GB can run Qwen 3.5 35B A3B with a S grade (Runs well). Expected decode speed: 75.0 tok/s.

How much VRAM does Qwen 3.5 35B A3B need?

Qwen 3.5 35B A3B (35B parameters) requires approximately 28.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.5 35B A3B?

The recommended quantization for Qwen 3.5 35B A3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.5 35B A3B run at on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Qwen 3.5 35B A3B achieves approximately 75.0 tokens per second decode speed with a time-to-first-token of 2580ms using Q4_K_M quantization.

Can NVIDIA A40 48GB run Qwen 3.5 35B A3B for coding?

For coding workloads, Qwen 3.5 35B A3B on NVIDIA A40 48GB receives a S grade with 75.0 tok/s and 131K context.

What context window can Qwen 3.5 35B A3B use on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Qwen 3.5 35B A3B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.