Can granite 8b code instruct 4k run on GTX 1080 Ti 11GB?

YES — Runs Great

B55Good

Estimated from fit model

granite 8b code instruct 4k needs ~8.1 GB VRAM. GTX 1080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~59 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) — 8.1 GB, 58.5 tok/s, Runs well

8.1 GB required11.0 GB available

74% VRAM used

Fit status

Runs well

Decode

58.5 tok/s

TTFT

3308 ms

Safe context

65K

Memory

8.1 GB / 11.0 GB

Memory breakdown

Weights4.9 GB

KV Cache0.9 GB

Runtime1.2 GB

Headroom1.1 GB

See how fast it feels

See how fast it feelsgranite 8b code instruct 4k 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: 58.5 tok/s decode · 3.3s TTFT (warm) · 146 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	B	Runs well	58.5 tok/s	1805 ms	65K
Coding	B	Runs well	58.5 tok/s	3308 ms	65K
Agentic Coding	C	Tight fit	58.5 tok/s	4812 ms	65K
Reasoning	B	Runs well	58.5 tok/s	3910 ms	65K
RAG	C	Tight fit	58.5 tok/s	6015 ms	65K

Quantization options

How granite 8b code instruct 4k (8B params) fits at each quantization level on GTX 1080 Ti 11GB (11.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C50
Q3_K_S	3	3.9 GB	Low	C51
NVFP4	4

Get started

Copy-paste commands to run granite 8b code instruct 4k on your machine.

Run

lms load hf-ibm-granite--granite-8b-code-instruct-4k-gguf && lms server start

Upgrade options

Hardware that runs granite 8b code instruct 4k well

RTX 5070 12GBBudget pick

12 GB VRAM (+1)672 GB/s (+188)

Raises estimated decode speed by about 48%.86.8 tok/s decode

Raises estimated decode speed by about 48%.

~$549 MSRP

RTX 4070 Super 12GBBest value

12 GB VRAM (+1)504 GB/s (+20)

Raises estimated decode speed by about 36%.79.5 tok/s decode

Raises estimated decode speed by about 36%.

~$599 MSRP

RTX 4070 12GBNVIDIA upgrade

12 GB VRAM (+1)504 GB/s (+20)

Raises estimated decode speed by about 32%.77.5 tok/s decode

Raises estimated decode speed by about 32%.

~$599 MSRP

Frequently asked questions

Can GTX 1080 Ti 11GB run granite 8b code instruct 4k?

Yes, GTX 1080 Ti 11GB can run granite 8b code instruct 4k with a B grade (Runs well). Expected decode speed: 58.5 tok/s.

How much VRAM does granite 8b code instruct 4k need?

granite 8b code instruct 4k (8B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.

What is the best quantization for granite 8b code instruct 4k?

The recommended quantization for granite 8b code instruct 4k is Q4_K_M, which balances quality and memory efficiency.

What speed will granite 8b code instruct 4k run at on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, granite 8b code instruct 4k achieves approximately 58.5 tokens per second decode speed with a time-to-first-token of 3308ms using Q4_K_M quantization.

Can GTX 1080 Ti 11GB run granite 8b code instruct 4k for coding?

For coding workloads, granite 8b code instruct 4k on GTX 1080 Ti 11GB receives a B grade with 58.5 tok/s and 65K context.

What context window can granite 8b code instruct 4k use on GTX 1080 Ti 11GB?

On GTX 1080 Ti 11GB, granite 8b code instruct 4k can safely use up to 65K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for GTX 1080 Ti 11GB See all hardware for granite 8b code instruct 4k

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