Can Granite 4.1 30B run on NVIDIA A100 40GB?

YES — Runs Great

S88Excellent
Estimated from fit model

Granite 4.1 30B needs ~27.4 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~77 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) 27.4 GB, 76.7 tok/s, Runs well
27.4 GB required40.0 GB available
69% VRAM used

Fit status

Runs well

Decode

76.7 tok/s

TTFT

2523 ms

Safe context

68K

Memory

27.4 GB / 40.0 GB

Memory breakdown

Weights18.3 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom4.0 GB

See how fast it feels

See how fast it feelsGranite 4.1 30B on NVIDIA A100 40GB
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: 76.7 tok/s decode · 2.5s TTFT (warm) · 192 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
ChatSRuns well76.7 tok/s1376 ms68K
CodingSRuns well76.7 tok/s2523 ms68K
Agentic CodingSRuns well76.7 tok/s3670 ms68K
ReasoningSRuns well76.7 tok/s2982 ms68K
RAGSRuns well76.7 tok/s4587 ms68K

Quantization options

How Granite 4.1 30B (30B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA77
Q3_K_S
3
14.7 GB
LowA78
NVFP4
4
16.8 GB
MediumA79
Q4_K_M
4
18.3 GB
MediumA80
Q5_K_M
5
21.6 GB
HighA81
Q6_K
6
24.6 GB
HighA81
Q8_0Best for your GPU
8
32.1 GB
Very HighA80
F16
16
61.5 GB
MaximumF0

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 40GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS197.5 tok/s
AlibabaQwen 3.6 35B A3B35BS166 tok/s
AlibabaQwen 3.5 35B A3B35BS180.5 tok/s
AlibabaQwen 3 32B32BS72.8 tok/s
AlibabaQwen 3 30B A3B30.5BS197.5 tok/s

Frequently asked questions

Can NVIDIA A100 40GB run Granite 4.1 30B?

Yes, NVIDIA A100 40GB can run Granite 4.1 30B with a S grade (Runs well). Expected decode speed: 76.7 tok/s.

How much VRAM does Granite 4.1 30B need?

Granite 4.1 30B (30B parameters) requires approximately 27.4 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 40GB?

On NVIDIA A100 40GB, Granite 4.1 30B achieves approximately 76.7 tokens per second decode speed with a time-to-first-token of 2523ms using Q4_K_M quantization.

Can NVIDIA A100 40GB run Granite 4.1 30B for coding?

For coding workloads, Granite 4.1 30B on NVIDIA A100 40GB receives a S grade with 76.7 tok/s and 68K context.

What context window can Granite 4.1 30B use on NVIDIA A100 40GB?

On NVIDIA A100 40GB, Granite 4.1 30B can safely use up to 68K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA A100 40GBSee all hardware for Granite 4.1 30B
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