Can Nemotron Cascade 2 30B A3B run on NVIDIA L40 48GB?

YES — Runs Great

S92Excellent

Estimated — low-sample bucket· few comparable runs

Nemotron Cascade 2 30B A3B needs ~26.9 GB VRAM. NVIDIA L40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~104 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced

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) — 26.9 GB, 104.2 tok/s, Runs well

26.9 GB required48.0 GB available

56% VRAM used

Fit status

Runs well

Decode

104.2 tok/s

TTFT

1858 ms

Safe context

131K

Memory

26.9 GB / 48.0 GB

Memory breakdown

Weights18.3 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom4.8 GB

See how fast it feels

See how fast it feelsNemotron Cascade 2 30B A3B on NVIDIA L40 48GB
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: 104.2 tok/s decode · 1.9s TTFT (warm) · 260 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs well	104.2 tok/s	1014 ms	131K
Coding	S	Runs well	104.2 tok/s	1858 ms	131K
Agentic Coding	S	Runs well	104.2 tok/s	2703 ms	131K
Reasoning	S	Runs well	104.2 tok/s	2196 ms	131K
RAG	S	Runs well	104.2 tok/s	3379 ms	131K

Quantization options

How Nemotron Cascade 2 30B A3B (30B params) fits at each quantization level on NVIDIA L40 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	11.7 GB	Low	A81
Q3_K_S	3	14.7 GB	Low	A82
NVFP4	4	16.8 GB	Medium	A83
Q4_K_M	4	18.3 GB	Medium	A83
Q5_K_M	5	21.6 GB	High	A84
Q6_K	6	24.6 GB	High	S86
Q8_0Best for your GPU	8	32.1 GB	Very High	S86
F16	16	61.5 GB	Maximum	F0

Get started

Copy-paste commands to run Nemotron Cascade 2 30B A3B on your machine.

Run

ollama run nemotron-cascade-2

Your hardware

More models your NVIDIA L40 48GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	73.4 tok/s
Qwen 3.6 35B A3B	35B	S	91.6 tok/s
Qwen 3.5 35B A3B	35B	S	99.7 tok/s
Qwen 3 32B	32B	S	19.2 tok/s
Qwen 3 30B A3B	30.5B	S	73.4 tok/s

Frequently asked questions

Can NVIDIA L40 48GB run Nemotron Cascade 2 30B A3B?

Yes, NVIDIA L40 48GB can run Nemotron Cascade 2 30B A3B with a S grade (Runs well). Expected decode speed: 104.2 tok/s.

How much VRAM does Nemotron Cascade 2 30B A3B need?

Nemotron Cascade 2 30B A3B (30B parameters) requires approximately 26.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Nemotron Cascade 2 30B A3B?

The recommended quantization for Nemotron Cascade 2 30B A3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Nemotron Cascade 2 30B A3B run at on NVIDIA L40 48GB?

On NVIDIA L40 48GB, Nemotron Cascade 2 30B A3B achieves approximately 104.2 tokens per second decode speed with a time-to-first-token of 1858ms using Q4_K_M quantization.

Can NVIDIA L40 48GB run Nemotron Cascade 2 30B A3B for coding?

For coding workloads, Nemotron Cascade 2 30B A3B on NVIDIA L40 48GB receives a S grade with 104.2 tok/s and 131K context.

What context window can Nemotron Cascade 2 30B A3B use on NVIDIA L40 48GB?

On NVIDIA L40 48GB, Nemotron Cascade 2 30B A3B can safely use up to 131K tokens of context. The model's official context limit is 262K, but available memory constrains the safe maximum.

See all results for NVIDIA L40 48GB See all hardware for Nemotron Cascade 2 30B A3B

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Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

104.2 tok/s

1014 ms

131K

Coding

Runs well

104.2 tok/s

1858 ms

131K

Agentic Coding

Runs well

104.2 tok/s

2703 ms

131K

Reasoning

Runs well

104.2 tok/s

2196 ms

131K

RAG

Runs well

104.2 tok/s

3379 ms

131K

Quantization options

How Nemotron Cascade 2 30B A3B (30B params) fits at each quantization level on NVIDIA L40 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	11.7 GB	Low	A81
Q3_K_S	3	14.7 GB	Low	A82
NVFP4	4	16.8 GB	Medium	A83
Q4_K_M	4	18.3 GB	Medium	A83
Q5_K_M	5	21.6 GB	High	A84
Q6_K	6	24.6 GB	High	S86
Q8_0Best for your GPU	8	32.1 GB	Very High	S86
F16	16	61.5 GB	Maximum	F0

Model

Params

Grade

Decode

Capabilities

Qwen3-Coder 30B A3B Instruct

30.5B

73.4 tok/s

Qwen 3.6 35B A3B

35B

91.6 tok/s

Qwen 3.5 35B A3B

35B

99.7 tok/s

Qwen 3 32B

32B

19.2 tok/s

Qwen 3 30B A3B