Will It Run AI

Can Granite 3.1 8B run on NVIDIA A10 24GB?

YES — Runs Great

B56Good
Estimated from fit model

Granite 3.1 8B needs ~10.4 GB VRAM. NVIDIA A10 24GB has 24.0 GB. With Q4_K_M quantization, expect ~96 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
Share:

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) 10.4 GB, 103.1 tok/s, Runs well
10.4 GB required24.0 GB available
43% VRAM used

Fit status

Runs well

Decode

103.1 tok/s

TTFT

1878 ms

Safe context

127K

Memory

10.4 GB / 24.0 GB

Memory breakdown

Weights4.9 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom2.4 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on NVIDIA A10 24GB
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

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well103.1 tok/s1024 ms127K
CodingBRuns well95.9 tok/s2019 ms127K
Agentic CodingBRuns well103.1 tok/s2731 ms127K
ReasoningBRuns well103.1 tok/s2219 ms127K
RAGBRuns well103.1 tok/s3414 ms127K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on NVIDIA A10 24GB (24.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowC49
Q3_K_S
3
3.9 GB
LowC49
NVFP4
4
4.5 GB
MediumC50
Q4_K_M
4
4.9 GB
MediumC50
Q5_K_M
5
5.8 GB
HighC51
Q6_K
6
6.6 GB
HighC51
Q8_0
8
8.6 GB
Very HighC52
F16Best for your GPU
16
16.4 GB
MaximumC54

Get started

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

Run

ollama run granite3.1-dense

Frequently asked questions

Can NVIDIA A10 24GB run Granite 3.1 8B?

Yes, NVIDIA A10 24GB can run Granite 3.1 8B with a B grade (Runs well). Expected decode speed: 95.9 tok/s.

How much VRAM does Granite 3.1 8B need?

Granite 3.1 8B (8B parameters) requires approximately 10.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 3.1 8B?

The recommended quantization for Granite 3.1 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 3.1 8B run at on NVIDIA A10 24GB?

On NVIDIA A10 24GB, Granite 3.1 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 A10 24GB run Granite 3.1 8B for coding?

For coding workloads, Granite 3.1 8B on NVIDIA A10 24GB receives a B grade with 95.9 tok/s and 127K context.

What context window can Granite 3.1 8B use on NVIDIA A10 24GB?

On NVIDIA A10 24GB, Granite 3.1 8B can safely use up to 127K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for NVIDIA A10 24GBSee all hardware for Granite 3.1 8B
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/granite-3.1-8b-on-a10-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: