Will It Run AI

Can Granite 4.1 8B run on RTX 4000 Ada 20GB?

YES — Runs Great

A76Great
Estimated from fit model

Granite 4.1 8B needs ~10.5 GB VRAM. RTX 4000 Ada 20GB has 20.0 GB. With Q4_K_M quantization, expect ~62 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced
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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) 10.5 GB, 61.9 tok/s, Runs well
10.5 GB required20.0 GB available
53% VRAM used

Fit status

Runs well

Decode

61.9 tok/s

TTFT

3130 ms

Safe context

78K

Memory

10.5 GB / 20.0 GB

Memory breakdown

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

See how fast it feels

See how fast it feelsGranite 4.1 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: 61.9 tok/s decode · 3.1s TTFT (warm) · 155 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
ChatARuns well61.9 tok/s1707 ms78K
CodingARuns well61.9 tok/s3130 ms78K
Agentic CodingARuns well61.9 tok/s4552 ms78K
ReasoningARuns well61.9 tok/s3699 ms78K
RAGARuns well61.9 tok/s5691 ms78K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowB70
Q3_K_S
3
3.9 GB
LowA70
NVFP4
4
4.5 GB
MediumA71
Q4_K_M
4
4.9 GB
MediumA71
Q5_K_M
5
5.8 GB
HighA72
Q6_K
6
6.6 GB
HighA72
Q8_0Best for your GPU
8
8.6 GB
Very HighA74
F16
16
16.4 GB
MaximumF0

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 RTX 4000 Ada 20GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BA23.2 tok/s
AlibabaQwen 3.5 27B27BA10.4 tok/s
AlibabaQwen 3.6 27B27BS13 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BA24.6 tok/s
AlibabaQwen 3.5 9B9BS55 tok/s

Frequently asked questions

Can RTX 4000 Ada 20GB run Granite 4.1 8B?

Yes, RTX 4000 Ada 20GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 61.9 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.5 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 RTX 4000 Ada 20GB?

On RTX 4000 Ada 20GB, Granite 4.1 8B achieves approximately 61.9 tokens per second decode speed with a time-to-first-token of 3130ms using Q4_K_M quantization.

Can RTX 4000 Ada 20GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on RTX 4000 Ada 20GB receives a A grade with 61.9 tok/s and 78K context.

What context window can Granite 4.1 8B use on RTX 4000 Ada 20GB?

On RTX 4000 Ada 20GB, Granite 4.1 8B can safely use up to 78K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX 4000 Ada 20GBSee all hardware for Granite 4.1 8B
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