Can Granite 3.1 8B run on NVIDIA A16 64GB?

YES — Runs Great

C51Usable

○Estimated from fit model

Granite 3.1 8B needs ~14.4 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~103 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) — 14.4 GB, 103.1 tok/s, Runs well

14.4 GB required64.0 GB available

23% VRAM used

Fit status

Runs well

Decode

103.1 tok/s

TTFT

1878 ms

Safe context

128K

Memory

14.4 GB / 64.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime1.2 GB

Headroom6.4 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on NVIDIA A16 64GB
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: 103.1 tok/s decode · 1.9s TTFT (warm) · 258 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	C	Runs well	103.1 tok/s	1024 ms	128K
Coding	C	Runs well	103.1 tok/s	1878 ms	128K
Agentic Coding	C	Runs well	103.1 tok/s	2731 ms	128K
Reasoning	C	Runs well	103.1 tok/s	2219 ms	128K
RAG	C	Runs well	103.1 tok/s	3414 ms	128K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C45
Q3_K_S	3	3.9 GB	Low	C45
NVFP4	4	4.5 GB	Medium	C45
Q4_K_M	4	4.9 GB	Medium	C45
Q5_K_M	5	5.8 GB	High	C45
Q6_K	6	6.6 GB	High	C45
Q8_0	8	8.6 GB	Very High	C46
F16Best for your GPU	16	16.4 GB	Maximum	C47