Can Qwen 3.6 35B A3B run on RTX PRO 6000 Blackwell Server Edition 96GB?

YES — Runs Great

S93Excellent

○Estimated from fit model

Qwen 3.6 35B A3B needs ~37.7 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~171 tok/s.

Runtime: SGLangCapacity: RoomyBandwidth: HighStack: OptimizedBottleneck: 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) — 37.7 GB, 170.5 tok/s, Runs well

37.7 GB required96.0 GB available

39% VRAM used

Fit status

Runs well

Decode

170.5 tok/s

TTFT

1136 ms

Safe context

244K

Memory

37.7 GB / 96.0 GB

Memory breakdown

Weights21.3 GB

KV Cache4.1 GB

Runtime2.6 GB

Headroom9.6 GB

See how fast it feels

See how fast it feelsQwen 3.6 35B A3B on RTX PRO 6000 Blackwell Server Edition 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: 170.5 tok/s decode · 1.1s TTFT (warm) · 426 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	170.5 tok/s	619 ms	244K
Coding	S	Runs well	170.5 tok/s	1136 ms	244K
Agentic Coding	S	Runs well	170.5 tok/s	1652 ms	244K
Reasoning	S	Runs well	170.5 tok/s	1342 ms	244K
RAG	S	Runs well	170.5 tok/s	2065 ms	244K

Quantization options

How Qwen 3.6 35B A3B (35B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	13.7 GB	Low	A82
Q3_K_S	3	17.2 GB	Low	A83
NVFP4	4

Get started

Copy-paste commands to run Qwen 3.6 35B A3B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
 --hf-repo "Qwen/Qwen3.6-35B-A3B" \
 --hf-file "Qwen3.6-35B-A3B-Q4_K_M.gguf" \
 -c 4096 -ngl 99

Your hardware

More models your RTX PRO 6000 Blackwell Server Edition 96GB can run

Model	Params	Grade	Decode	Capabilities
👁 Alibaba Qwen 3.5 122B A10B	122B	S	53.9 tok/s

Frequently asked questions

See all results for RTX PRO 6000 Blackwell Server Edition 96GB See all hardware for Qwen 3.6 35B A3B

URL: https://willitrunai.com/can-run/qwen-3.6-35b-a3b-on-rtx-pro-6000-blackwell-server-96gb

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