Can Granite 3.1 8B run on RTX 4000 Ada 20GB?

YES — Runs Great

B56Good

Estimated from fit model

Granite 3.1 8B needs ~9.7 GB VRAM. RTX 4000 Ada 20GB has 20.0 GB. With Q4_K_M quantization, expect ~71 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) — 9.7 GB, 71.1 tok/s, Runs well

9.7 GB required20.0 GB available

49% VRAM used

Fit status

Runs well

Decode

71.1 tok/s

TTFT

2722 ms

Safe context

100K

Memory

9.7 GB / 20.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom2.0 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on RTX 4000 Ada 20GB
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: 71.1 tok/s decode · 2.7s TTFT (warm) · 178 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	71.1 tok/s	1485 ms	100K
Coding	B	Runs well	71.1 tok/s	2722 ms	100K
Agentic Coding	B	Runs well	71.1 tok/s	3959 ms	100K
Reasoning	B	Runs well	71.1 tok/s	3216 ms	100K
RAG	B	Runs well	71.1 tok/s	4948 ms	100K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C50
Q3_K_S	3	3.9 GB	Low	C51
NVFP4	4	4.5 GB	Medium	C51
Q4_K_M	4	4.9 GB	Medium	C51
Q5_K_M	5	5.8 GB	High	C52
Q6_K	6	6.6 GB	High	C53
Q8_0Best for your GPU	8	8.6 GB	Very High	C54
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

Frequently asked questions

Can RTX 4000 Ada 20GB run Granite 3.1 8B?

Yes, RTX 4000 Ada 20GB can run Granite 3.1 8B with a B grade (Runs well). Expected decode speed: 71.1 tok/s.

How much VRAM does Granite 3.1 8B need?

Granite 3.1 8B (8B parameters) requires approximately 9.7 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 4000 Ada 20GB?

On RTX 4000 Ada 20GB, Granite 3.1 8B achieves approximately 71.1 tokens per second decode speed with a time-to-first-token of 2722ms using Q4_K_M quantization.

Can RTX 4000 Ada 20GB run Granite 3.1 8B for coding?

For coding workloads, Granite 3.1 8B on RTX 4000 Ada 20GB receives a B grade with 71.1 tok/s and 100K context.

What context window can Granite 3.1 8B use on RTX 4000 Ada 20GB?

On RTX 4000 Ada 20GB, Granite 3.1 8B can safely use up to 100K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RTX 4000 Ada 20GB See all hardware for Granite 3.1 8B

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