Can Qwen 3.5 35B A3B run on Gaudi 3 128GB?

YES — Runs Great

S90Excellent

Estimated from fit model

Qwen 3.5 35B A3B needs ~36.5 GB VRAM. Gaudi 3 128GB has 128.0 GB. With Q4_K_M quantization, expect ~358 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 36.5 GB, 357.9 tok/s, Runs well

36.5 GB required128.0 GB available

29% VRAM used

Fit status

Runs well

Decode

357.9 tok/s

TTFT

541 ms

Safe context

131K

Memory

36.5 GB / 128.0 GB

Memory breakdown

Weights21.3 GB

KV Cache1.5 GB

Runtime0.9 GB

Headroom12.8 GB

See how fast it feels

See how fast it feelsQwen 3.5 35B A3B on Gaudi 3 128GB
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: 357.9 tok/s decode · 541ms TTFT (warm) · 895 tok/s prefill

What limits this setup

The raw memory story may look fine, but the software ecosystem is still a constraint here.

Runtime ecosystem is narrower than CUDA

Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.

Best improvement path

Prefer CUDA if you want the path of least resistance

If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs well	357.9 tok/s	350 ms	131K
Coding	S	Runs well	357.9 tok/s	541 ms	131K
Agentic Coding	S	Runs well	357.9 tok/s	787 ms	131K
Reasoning	S	Runs well	357.9 tok/s	639 ms	131K
RAG	S	Runs well	357.9 tok/s	983 ms	131K

Quantization options

How Qwen 3.5 35B A3B (35B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.7 GB	Low	A80
Q3_K_S	3	17.2 GB	Low	A80
NVFP4	4	19.6 GB	Medium	A81
Q4_K_M	4	21.3 GB	Medium	A81
Q5_K_M	5	25.2 GB	High	A81
Q6_K	6	28.7 GB	High	A82
Q8_0	8	37.5 GB	Very High	A83
F16Best for your GPU	16	71.8 GB	Maximum	S89

Get started

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

Run

ollama run qwen3.5:35b-a3b

Your hardware

More models your Gaudi 3 128GB can run

Model	Params	Grade	Decode	Capabilities
Devstral 2 123B Instruct	123B	S	37.5 tok/s
Qwen 3.5 122B A10B	122B	S	104.1 tok/s

Frequently asked questions

Can Gaudi 3 128GB run Qwen 3.5 35B A3B?

Yes, Gaudi 3 128GB can run Qwen 3.5 35B A3B with a S grade (Runs well). Expected decode speed: 357.9 tok/s.

How much VRAM does Qwen 3.5 35B A3B need?

Qwen 3.5 35B A3B (35B parameters) requires approximately 36.5 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 Gaudi 3 128GB?

On Gaudi 3 128GB, Qwen 3.5 35B A3B achieves approximately 357.9 tokens per second decode speed with a time-to-first-token of 541ms using Q4_K_M quantization.

Can Gaudi 3 128GB run Qwen 3.5 35B A3B for coding?

For coding workloads, Qwen 3.5 35B A3B on Gaudi 3 128GB receives a S grade with 357.9 tok/s and 131K context.

What context window can Qwen 3.5 35B A3B use on Gaudi 3 128GB?

On Gaudi 3 128GB, 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.

What should I upgrade first if Qwen 3.5 35B A3B feels slow on Gaudi 3 128GB?

Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.

Would CUDA be a better path than Gaudi 3 128GB for Qwen 3.5 35B A3B?

Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.

See all results for Gaudi 3 128GB See all hardware for Qwen 3.5 35B A3B

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<iframe src="https://willitrunai.com/embed/qwen-3.5-35b-a3b-on-gaudi-3-128gb" 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

357.9 tok/s

350 ms

131K

Coding

Runs well

357.9 tok/s

541 ms

131K

Agentic Coding

Runs well

357.9 tok/s

787 ms

131K

Reasoning

Runs well

357.9 tok/s

639 ms

131K

RAG

Runs well

357.9 tok/s

983 ms

131K

Quantization options

How Qwen 3.5 35B A3B (35B params) fits at each quantization level on Gaudi 3 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.7 GB	Low	A80
Q3_K_S	3	17.2 GB	Low	A80
NVFP4	4	19.6 GB	Medium	A81
Q4_K_M	4	21.3 GB	Medium	A81
Q5_K_M	5	25.2 GB	High	A81
Q6_K	6	28.7 GB	High	A82
Q8_0	8	37.5 GB	Very High	A83
F16Best for your GPU	16	71.8 GB	Maximum	S89

Model

Params

Grade

Decode

Capabilities

Devstral 2 123B Instruct

123B

37.5 tok/s

Qwen 3.5 122B A10B

122B

104.1 tok/s

Frequently asked questions

Can Gaudi 3 128GB run Qwen 3.5 35B A3B?

Yes, Gaudi 3 128GB can run Qwen 3.5 35B A3B with a S grade (Runs well). Expected decode speed: 357.9 tok/s.

How much VRAM does Qwen 3.5 35B A3B need?

Qwen 3.5 35B A3B (35B parameters) requires approximately 36.5 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 Gaudi 3 128GB?

On Gaudi 3 128GB, Qwen 3.5 35B A3B achieves approximately 357.9 tokens per second decode speed with a time-to-first-token of 541ms using Q4_K_M quantization.

Can Gaudi 3 128GB run Qwen 3.5 35B A3B for coding?

For coding workloads, Qwen 3.5 35B A3B on Gaudi 3 128GB receives a S grade with 357.9 tok/s and 131K context.

What context window can Qwen 3.5 35B A3B use on Gaudi 3 128GB?

On Gaudi 3 128GB, 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.

What should I upgrade first if Qwen 3.5 35B A3B feels slow on Gaudi 3 128GB?

Would CUDA be a better path than Gaudi 3 128GB for Qwen 3.5 35B A3B?