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URL: https://willitrunai.com/can-run/granite-4.1-30b-on-a800-80gb


Can Granite 4.1 30B run on NVIDIA A800 80GB?

YES — Runs Great

A83Great
Estimated from fit model

Granite 4.1 30B needs ~31.4 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~89 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, 88.7 tok/s, Runs well
31.4 GB required80.0 GB available
39% VRAM used

Fit status

Runs well

Decode

88.7 tok/s

TTFT

2184 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 A800 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: 88.7 tok/s decode · 2.2s TTFT (warm) · 222 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 well88.7 tok/s1191 ms131K
CodingARuns well88.7 tok/s2184 ms131K
Agentic CodingARuns well88.7 tok/s3176 ms131K
ReasoningARuns well88.7 tok/s2581 ms131K
RAGARuns well88.7 tok/s3970 ms131K

Quantization options

How Granite 4.1 30B (30B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA73
Q3_K_S
3
14.7 GB
LowA73
NVFP4
4

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 A800 80GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BA15.5 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for NVIDIA A800 80GBSee all hardware for Granite 4.1 30B
16.8 GB
Medium
A74
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
228.2 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BA45.9 tok/s
👁 Alibaba
Qwen 3.6 35B A3B
35BS191.8 tok/s
👁 Alibaba
Qwen 3.5 35B A3B
35BS208.6 tok/s