Can Granite 4.1 8B run on NVIDIA A2 16GB?

YES — Runs Great

A76Great

Estimated from fit model

Granite 4.1 8B needs ~10.1 GB VRAM. NVIDIA A2 16GB has 16.0 GB. With Q4_K_M quantization, expect ~32 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: Very lowStack: BasicBottleneck: Memory bandwidth

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) — 10.1 GB, 34.4 tok/s, Runs well

10.1 GB required16.0 GB available

63% VRAM used

Fit status

Runs well

Decode

34.4 tok/s

TTFT

5634 ms

Safe context

55K

Memory

10.1 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGranite 4.1 8B on NVIDIA A2 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: 34.4 tok/s decode · 5.6s TTFT (warm) · 86 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	34.4 tok/s	3073 ms	55K
Coding	A	Runs well	32.0 tok/s	6056 ms	55K
Agentic Coding	A	Runs well	34.4 tok/s	8194 ms	55K
Reasoning	A	Runs well	34.4 tok/s	6658 ms	55K
RAG	A	Runs well	34.4 tok/s	10243 ms	55K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on NVIDIA A2 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	A71
Q3_K_S	3	3.9 GB	Low	A72
NVFP4	4

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 NVIDIA A2 16GB can run

Model	Params	Grade	Decode	Capabilities
Qwen 3.5 9B	9B	S	30.5 tok/s
Qwen 3 14B	14B	S	19.7 tok/s

Frequently asked questions

Can NVIDIA A2 16GB run Granite 4.1 8B?

Yes, NVIDIA A2 16GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 32.0 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 4.1 8B?

The recommended quantization for Granite 4.1 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 4.1 8B run at on NVIDIA A2 16GB?

On NVIDIA A2 16GB, Granite 4.1 8B achieves approximately 32.0 tokens per second decode speed with a time-to-first-token of 6056ms using Q4_K_M quantization.

Can NVIDIA A2 16GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on NVIDIA A2 16GB receives a A grade with 32.0 tok/s and 55K context.

What context window can Granite 4.1 8B use on NVIDIA A2 16GB?

On NVIDIA A2 16GB, Granite 4.1 8B can safely use up to 55K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A2 16GB See all hardware for Granite 4.1 8B

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