Can Granite 3.1 8B run on RTX 2000 Ada 16GB?

YES — Runs Great

B57Good

Estimated from fit model

Granite 3.1 8B needs ~9.3 GB VRAM. RTX 2000 Ada 16GB has 16.0 GB. With Q4_K_M quantization, expect ~55 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: 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) — 9.3 GB, 55.4 tok/s, Runs well

9.3 GB required16.0 GB available

58% VRAM used

Fit status

Runs well

Decode

55.4 tok/s

TTFT

3492 ms

Safe context

71K

Memory

9.3 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on RTX 2000 Ada 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: 55.4 tok/s decode · 3.5s TTFT (warm) · 139 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	B	Runs well	55.4 tok/s	1904 ms	71K
Coding	B	Runs well	55.4 tok/s	3492 ms	71K
Agentic Coding	B	Runs well	55.4 tok/s	5079 ms	71K
Reasoning	B	Runs well	55.4 tok/s	4126 ms	71K
RAG	B	Runs well	55.4 tok/s	6348 ms	71K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on RTX 2000 Ada 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C52
Q3_K_S	3	3.9 GB	Low	C52
NVFP4	4	4.5 GB	Medium	C53
Q4_K_M	4	4.9 GB	Medium	C53
Q5_K_M	5	5.8 GB	High	C54
Q6_K	6	6.6 GB	High	C55
Q8_0Best for your GPU	8	8.6 GB	Very High	B56
F16	16	16.4 GB	Maximum	F0

Get started

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

Run

ollama run granite3.1-dense

Upgrade options

Hardware that runs Granite 3.1 8B well

MacBook Pro M4 Pro 24GBBudget pick

24 GB Unified (+8)

This setup is broadly balanced for this model.53.3 tok/s decode

~$1,999 MSRP

Frequently asked questions

Can RTX 2000 Ada 16GB run Granite 3.1 8B?

Yes, RTX 2000 Ada 16GB can run Granite 3.1 8B with a B grade (Runs well). Expected decode speed: 55.4 tok/s.

How much VRAM does Granite 3.1 8B need?

Granite 3.1 8B (8B parameters) requires approximately 9.3 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 RTX 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Granite 3.1 8B achieves approximately 55.4 tokens per second decode speed with a time-to-first-token of 3492ms using Q4_K_M quantization.

Can RTX 2000 Ada 16GB run Granite 3.1 8B for coding?

For coding workloads, Granite 3.1 8B on RTX 2000 Ada 16GB receives a B grade with 55.4 tok/s and 71K context.

What context window can Granite 3.1 8B use on RTX 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Granite 3.1 8B can safely use up to 71K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RTX 2000 Ada 16GB See all hardware for Granite 3.1 8B

Embed this result▼

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<iframe src="https://willitrunai.com/embed/granite-3.1-8b-on-rtx-2000-ada-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

55.4 tok/s

1904 ms

71K

Coding

Runs well

55.4 tok/s

3492 ms

71K

Agentic Coding

Runs well

55.4 tok/s

5079 ms

71K

Reasoning

Runs well

55.4 tok/s

4126 ms

71K

RAG

Runs well

55.4 tok/s

6348 ms

71K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on RTX 2000 Ada 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C52
Q3_K_S	3	3.9 GB	Low	C52
NVFP4	4	4.5 GB	Medium	C53
Q4_K_M	4	4.9 GB	Medium	C53
Q5_K_M	5	5.8 GB	High	C54
Q6_K	6	6.6 GB	High	C55
Q8_0Best for your GPU	8	8.6 GB	Very High	B56
F16	16	16.4 GB	Maximum	F0

Frequently asked questions

Can RTX 2000 Ada 16GB run Granite 3.1 8B?

Yes, RTX 2000 Ada 16GB can run Granite 3.1 8B with a B grade (Runs well). Expected decode speed: 55.4 tok/s.

How much VRAM does Granite 3.1 8B need?

Granite 3.1 8B (8B parameters) requires approximately 9.3 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 RTX 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Granite 3.1 8B achieves approximately 55.4 tokens per second decode speed with a time-to-first-token of 3492ms using Q4_K_M quantization.

Can RTX 2000 Ada 16GB run Granite 3.1 8B for coding?

For coding workloads, Granite 3.1 8B on RTX 2000 Ada 16GB receives a B grade with 55.4 tok/s and 71K context.

What context window can Granite 3.1 8B use on RTX 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Granite 3.1 8B can safely use up to 71K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.