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

YES — Runs Great

A72Great

Estimated from fit model

Granite Code 8B needs ~14.4 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~96 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

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 Code 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	A	Runs well	95.9 tok/s	1101 ms	8K
Coding	A	Runs well	95.9 tok/s	2019 ms	8K
Agentic Coding	A	Runs well	95.9 tok/s	2936 ms	8K
Reasoning	A	Runs well	95.9 tok/s	2386 ms	8K
RAG	A	Runs well	95.9 tok/s	3670 ms	8K

Quantization options

How Granite Code 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	B66
Q3_K_S	3	3.9 GB	Low	B66
NVFP4	4	4.5 GB	Medium	B66
Q4_K_M	4	4.9 GB	Medium	B66
Q5_K_M	5	5.8 GB	High	B66
Q6_K	6	6.6 GB	High	B66
Q8_0	8	8.6 GB	Very High	B66
F16Best for your GPU	16	16.4 GB	Maximum	B68

Get started

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

Run

ollama run granite-code:8b

Your hardware

More models your NVIDIA A16 64GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	70.8 tok/s
Qwen 3.5 27B	27B	S	30.7 tok/s
Qwen 3.6 27B	27B	S	30.8 tok/s
Qwen 3.6 35B A3B	35B	S	59.5 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	73.2 tok/s

Frequently asked questions

Can NVIDIA A16 64GB run Granite Code 8B?

Yes, NVIDIA A16 64GB can run Granite Code 8B with a A grade (Runs well). Expected decode speed: 95.9 tok/s.

How much VRAM does Granite Code 8B need?

Granite Code 8B (8B parameters) requires approximately 14.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 8B?

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

What speed will Granite Code 8B run at on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Granite Code 8B achieves approximately 95.9 tokens per second decode speed with a time-to-first-token of 2019ms using Q4_K_M quantization.

Can NVIDIA A16 64GB run Granite Code 8B for coding?

For coding workloads, Granite Code 8B on NVIDIA A16 64GB receives a A grade with 95.9 tok/s and 8K context.

What context window can Granite Code 8B use on NVIDIA A16 64GB?

On NVIDIA A16 64GB, Granite Code 8B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for NVIDIA A16 64GB See all hardware for Granite Code 8B

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