Can Granite 4.1 8B run on RTX A4500 20GB?

YES — Runs Great

A77Great

○Estimated from fit model

Granite 4.1 8B needs ~10.5 GB VRAM. RTX A4500 20GB has 20.0 GB. With Q4_K_M quantization, expect ~110 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) — 10.5 GB, 110.0 tok/s, Runs well

10.5 GB required20.0 GB available

53% VRAM used

Fit status

Runs well

Decode

110.0 tok/s

TTFT

1761 ms

Safe context

78K

Memory

10.5 GB / 20.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom2.0 GB

See how fast it feels

See how fast it feelsGranite 4.1 8B on RTX A4500 20GB
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: 110.0 tok/s decode · 1.8s TTFT (warm) · 275 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	A	Runs well	110.0 tok/s	960 ms	78K
Coding	A	Runs well	110.0 tok/s	1761 ms	78K
Agentic Coding	A	Runs well	110.0 tok/s	2561 ms	78K
Reasoning	A	Runs well	110.0 tok/s	2081 ms	78K
RAG	A	Runs well	110.0 tok/s	3201 ms	78K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	B70
Q3_K_S	3	3.9 GB	Low	A70
NVFP4	4	4.5 GB	Medium	A71
Q4_K_M	4	4.9 GB	Medium	A71
Q5_K_M	5	5.8 GB	High	A72
Q6_K	6	6.6 GB	High	A72
Q8_0Best for your GPU	8	8.6 GB	Very High	A74
F16	16	16.4 GB	Maximum	F0

Get started

Copy-paste commands to run Granite 4.1 8B on your machine.

Run

ollama run granite4.1:8b

Your hardware

More models your RTX A4500 20GB can run

Model	Params	Grade	Decode
👁 Alibaba Qwen3-Coder 30B A3B Instruct	30.5B	A	41.2 tok/s
👁 Alibaba Qwen 3.5 27B	27B	A	18.6 tok/s
👁 Alibaba Qwen 3.6 27B	27B	S	23 tok/s
👁 Alibaba Qwen3-VL 30B A3B Instruct	30B	A	43.8 tok/s
👁 Alibaba Qwen 3.5 9B	9B	S	97.7 tok/s

Frequently asked questions

See all results for RTX A4500 20GB See all hardware for Granite 4.1 8B

URL: https://willitrunai.com/can-run/granite-4.1-8b-on-rtx-a4500-20gb