Can Qwen 3.5 9B run on GTX 1080 Ti 11GB?

YES — Tight Fit

S94Excellent

Estimated from fit model

Qwen 3.5 9B needs ~10.0 GB VRAM. GTX 1080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~56 tok/s.

Runtime: OllamaCapacity: TightBandwidth: 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) — 10.0 GB, 55.9 tok/s, Tight fit

10.0 GB required11.0 GB available

91% VRAM used

Fit status

Tight fit

Decode

55.9 tok/s

TTFT

3462 ms

Safe context

23K

Memory

10.0 GB / 11.0 GB

Memory breakdown

Weights5.5 GB

KV Cache2.2 GB

Runtime1.2 GB

Headroom1.1 GB

See how fast it feels

See how fast it feelsQwen 3.5 9B on GTX 1080 Ti 11GB
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: 55.9 tok/s decode · 3.5s TTFT (warm) · 140 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs well	55.9 tok/s	1889 ms	23K
Coding	S	Tight fit	55.9 tok/s	3462 ms	23K
Agentic Coding	A	Very compromised (needs ~0.5 GB host RAM)	32.6 tok/s	8643 ms	23K
Reasoning	S	Tight fit	55.9 tok/s	4092 ms	23K
RAG	A	Very compromised (needs ~0.5 GB host RAM)	32.6 tok/s	10804 ms	23K

Quantization options

How Qwen 3.5 9B (9B params) fits at each quantization level on GTX 1080 Ti 11GB (11.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	S92
Q3_K_S	3	4.4 GB	Low	S94
NVFP4	4	5.0 GB	Medium	S94
Q4_K_M	4	5.5 GB	Medium	S94
Q5_K_M	5	6.5 GB	High	S94
Q6_KBest for your GPU	6	7.4 GB	High	S93
Q8_0	8	9.6 GB	Very High	F0
F16	16	18.5 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 3.5 9B on your machine.

Run

ollama run qwen3.5:9b

Frequently asked questions

Can GTX 1080 Ti 11GB run Qwen 3.5 9B?

Yes, GTX 1080 Ti 11GB can run Qwen 3.5 9B with a S grade (Tight fit). Expected decode speed: 55.9 tok/s.

How much VRAM does Qwen 3.5 9B need?

Qwen 3.5 9B (9B parameters) requires approximately 10.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.5 9B?

The recommended quantization for Qwen 3.5 9B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.5 9B run at on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, Qwen 3.5 9B achieves approximately 55.9 tokens per second decode speed with a time-to-first-token of 3462ms using Q4_K_M quantization.

Can GTX 1080 Ti 11GB run Qwen 3.5 9B for coding?

For coding workloads, Qwen 3.5 9B on GTX 1080 Ti 11GB receives a S grade with 55.9 tok/s and 23K context.

What context window can Qwen 3.5 9B use on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, Qwen 3.5 9B can safely use up to 23K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for GTX 1080 Ti 11GB See all hardware for Qwen 3.5 9B

Embed this result▼

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<iframe src="https://willitrunai.com/embed/qwen-3.5-9b-on-gtx-1080-ti-11gb" 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

55.9 tok/s

1889 ms

23K

Coding

Tight fit

55.9 tok/s

3462 ms

23K

Agentic Coding

Very compromised (needs ~0.5 GB host RAM)

32.6 tok/s

8643 ms

23K

Reasoning

Tight fit

55.9 tok/s

4092 ms

23K

RAG

Very compromised (needs ~0.5 GB host RAM)

32.6 tok/s

10804 ms

23K

Quant

Bits

VRAM

Quality

Fit

Q2_K

3.5 GB

Low

S92

Q3_K_S

4.4 GB

Low

S94

NVFP4

5.0 GB

Medium

S94

Q4_K_M

5.5 GB

Medium

S94

Q5_K_M

6.5 GB

High

S94

Q6_KBest for your GPU

7.4 GB

High

S93

Q8_0

9.6 GB

Very High

F16

18.5 GB

Maximum

Frequently asked questions

Can GTX 1080 Ti 11GB run Qwen 3.5 9B?

Yes, GTX 1080 Ti 11GB can run Qwen 3.5 9B with a S grade (Tight fit). Expected decode speed: 55.9 tok/s.

How much VRAM does Qwen 3.5 9B need?

Qwen 3.5 9B (9B parameters) requires approximately 10.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.5 9B?

The recommended quantization for Qwen 3.5 9B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.5 9B run at on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, Qwen 3.5 9B achieves approximately 55.9 tokens per second decode speed with a time-to-first-token of 3462ms using Q4_K_M quantization.

Can GTX 1080 Ti 11GB run Qwen 3.5 9B for coding?

For coding workloads, Qwen 3.5 9B on GTX 1080 Ti 11GB receives a S grade with 55.9 tok/s and 23K context.

What context window can Qwen 3.5 9B use on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, Qwen 3.5 9B can safely use up to 23K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.