Will It Run AI

Can Granite 4.1 30B run on B100 192GB?

YES — Runs Great

A79Great
Estimated from fit model

Granite 4.1 30B needs ~42.6 GB VRAM. B100 192GB has 192.0 GB. With Q4_K_M quantization, expect ~395 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) 42.6 GB, 394.8 tok/s, Runs well
42.6 GB required192.0 GB available
22% VRAM used

Fit status

Runs well

Decode

394.8 tok/s

TTFT

490 ms

Safe context

131K

Memory

42.6 GB / 192.0 GB

Memory breakdown

Weights18.3 GB
KV Cache3.9 GB
Runtime1.2 GB
Headroom19.2 GB

See how fast it feels

See how fast it feelsGranite 4.1 30B on B100 192GB
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: 394.8 tok/s decode · 490ms TTFT (warm) · 987 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 well394.8 tok/s350 ms131K
CodingARuns well394.8 tok/s490 ms131K
Agentic CodingARuns well394.8 tok/s713 ms131K
ReasoningARuns well394.8 tok/s580 ms131K
RAGARuns well394.8 tok/s892 ms131K

Quantization options

How Granite 4.1 30B (30B params) fits at each quantization level on B100 192GB (192.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowB69
Q3_K_S
3
14.7 GB
LowB69
NVFP4
4
16.8 GB
MediumB70
Q4_K_M
4
18.3 GB
MediumB70
Q5_K_M
5
21.6 GB
HighA70
Q6_K
6
24.6 GB
HighA70
Q8_0
8
32.1 GB
Very HighA71
F16Best for your GPU
16
61.5 GB
MaximumA74

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 B100 192GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS97.4 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS1016.1 tok/s
AlibabaQwen 3.5 122B A10B122BS270.2 tok/s
DeepSeekDeepSeek V4 Flash284BS144.8 tok/s
AlibabaQwen 3.6 35B A3B35BS854 tok/s

Frequently asked questions

Can B100 192GB run Granite 4.1 30B?

Yes, B100 192GB can run Granite 4.1 30B with a A grade (Runs well). Expected decode speed: 394.8 tok/s.

How much VRAM does Granite 4.1 30B need?

Granite 4.1 30B (30B parameters) requires approximately 42.6 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 B100 192GB?

On B100 192GB, Granite 4.1 30B achieves approximately 394.8 tokens per second decode speed with a time-to-first-token of 490ms using Q4_K_M quantization.

Can B100 192GB run Granite 4.1 30B for coding?

For coding workloads, Granite 4.1 30B on B100 192GB receives a A grade with 394.8 tok/s and 131K context.

What context window can Granite 4.1 30B use on B100 192GB?

On B100 192GB, 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 B100 192GBSee all hardware for Granite 4.1 30B
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