Can Granite 3.1 8B run on RTX A4000 16GB?

YES — Runs Great

B58Good

○Estimated from fit model

Granite 3.1 8B needs ~9.3 GB VRAM. RTX A4000 16GB has 16.0 GB. With Q4_K_M quantization, expect ~79 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: 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) — 9.3 GB, 79.4 tok/s, Runs well

9.3 GB required16.0 GB available

58% VRAM used

Fit status

Runs well

Decode

79.4 tok/s

TTFT

2437 ms

Safe context

71K

Memory

9.3 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on RTX A4000 16GB
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: 79.4 tok/s decode · 2.4s TTFT (warm) · 199 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	B	Runs well	79.4 tok/s	1329 ms	71K
Coding	B	Runs well	79.4 tok/s	2437 ms	71K
Agentic Coding	B	Runs well	79.4 tok/s	3545 ms	71K
Reasoning	B	Runs well	79.4 tok/s	2880 ms	71K
RAG	B	Runs well	79.4 tok/s	4431 ms	71K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on RTX A4000 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C52
Q3_K_S	3	3.9 GB	Low	C52
NVFP4	4

Get started

Copy-paste commands to run Granite 3.1 8B on your machine.

Run

ollama run granite3.1-dense

Frequently asked questions

See all results for RTX A4000 16GB See all hardware for Granite 3.1 8B

URL: https://willitrunai.com/can-run/granite-3.1-8b-on-a4000-16gb

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