Can Granite 4.1 30B run on NVIDIA A100 80GB?

YES — Runs Great

A83Great
Estimated from fit model

Granite 4.1 30B needs ~31.4 GB VRAM. NVIDIA A100 80GB has 80.0 GB. With Q4_K_M quantization, expect ~101 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: 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) 31.4 GB, 100.6 tok/s, Runs well
31.4 GB required80.0 GB available
39% VRAM used

Fit status

Runs well

Decode

100.6 tok/s

TTFT

1924 ms

Safe context

131K

Memory

31.4 GB / 80.0 GB

Memory breakdown

Weights18.3 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsGranite 4.1 30B on NVIDIA A100 80GB
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: 100.6 tok/s decode · 1.9s TTFT (warm) · 252 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 well100.6 tok/s1050 ms131K
CodingARuns well100.6 tok/s1924 ms131K
Agentic CodingARuns well100.6 tok/s2799 ms131K
ReasoningARuns well100.6 tok/s2274 ms131K
RAGARuns well100.6 tok/s3499 ms131K

Quantization options

How Granite 4.1 30B (30B params) fits at each quantization level on NVIDIA A100 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA73
Q3_K_S
3
14.7 GB
LowA73
NVFP4
4
16.8 GB
MediumA74
Q4_K_M
4
18.3 GB
MediumA74
Q5_K_M
5
21.6 GB
HighA74
Q6_K
6
24.6 GB
HighA75
Q8_0
8
32.1 GB
Very HighA77
F16Best for your GPU
16
61.5 GB
MaximumA80

Get started

Copy-paste commands to run Granite 4.1 30B on your machine.

Run

ollama run granite4.1:30b

Your hardware

More models your NVIDIA A100 80GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BA17.6 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS259 tok/s
AlibabaQwen 3.5 122B A10B122BA52.1 tok/s
AlibabaQwen 3.6 35B A3B35BS217.7 tok/s
AlibabaQwen 3.5 35B A3B35BS236.7 tok/s

Frequently asked questions

Can NVIDIA A100 80GB run Granite 4.1 30B?

Yes, NVIDIA A100 80GB can run Granite 4.1 30B with a A grade (Runs well). Expected decode speed: 100.6 tok/s.

How much VRAM does Granite 4.1 30B need?

Granite 4.1 30B (30B parameters) requires approximately 31.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 4.1 30B?

The recommended quantization for Granite 4.1 30B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 4.1 30B run at on NVIDIA A100 80GB?

On NVIDIA A100 80GB, Granite 4.1 30B achieves approximately 100.6 tokens per second decode speed with a time-to-first-token of 1924ms using Q4_K_M quantization.

Can NVIDIA A100 80GB run Granite 4.1 30B for coding?

For coding workloads, Granite 4.1 30B on NVIDIA A100 80GB receives a A grade with 100.6 tok/s and 131K context.

What context window can Granite 4.1 30B use on NVIDIA A100 80GB?

On NVIDIA A100 80GB, Granite 4.1 30B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A100 80GBSee all hardware for Granite 4.1 30B
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