Can Granite 4.1 8B run on Tesla P40 24GB?

YES — Runs Great

A74Great

Estimated from fit model

Granite 4.1 8B needs ~10.9 GB VRAM. Tesla P40 24GB has 24.0 GB. With Q4_K_M quantization, expect ~45 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: 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) — 10.9 GB, 45.0 tok/s, Runs well

10.9 GB required24.0 GB available

45% VRAM used

Fit status

Runs well

Decode

45.0 tok/s

TTFT

4305 ms

Safe context

102K

Memory

10.9 GB / 24.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsGranite 4.1 8B on Tesla P40 24GB
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: 45.0 tok/s decode · 4.3s TTFT (warm) · 112 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	45.0 tok/s	2348 ms	102K
Coding	A	Runs well	45.0 tok/s	4305 ms	102K
Agentic Coding	A	Runs well	45.0 tok/s	6262 ms	102K
Reasoning	A	Runs well	45.0 tok/s	5088 ms	102K
RAG	A	Runs well	45.0 tok/s	7828 ms	102K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	B69
Q3_K_S	3	3.9 GB	Low	B69
NVFP4	4	4.5 GB	Medium	B69
Q4_K_M	4	4.9 GB	Medium	B70
Q5_K_M	5	5.8 GB	High	A70
Q6_K	6	6.6 GB	High	A71
Q8_0	8	8.6 GB	Very High	A72
F16Best for your GPU	16	16.4 GB	Maximum	A74

Get started

Copy-paste commands to run Granite 4.1 8B on your machine.

Run

ollama run granite4.1:8b

Your hardware

More models your Tesla P40 24GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	30.9 tok/s
Qwen 3.5 27B	27B	S	13.4 tok/s
Qwen 3.6 27B	27B	S	13.4 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	31.9 tok/s
Qwen 3.5 9B	9B	S	40 tok/s

Frequently asked questions

Can Tesla P40 24GB run Granite 4.1 8B?

Yes, Tesla P40 24GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 45.0 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 4.1 8B?

The recommended quantization for Granite 4.1 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 4.1 8B run at on Tesla P40 24GB?

On Tesla P40 24GB, Granite 4.1 8B achieves approximately 45.0 tokens per second decode speed with a time-to-first-token of 4305ms using Q4_K_M quantization.

Can Tesla P40 24GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on Tesla P40 24GB receives a A grade with 45.0 tok/s and 102K context.

What context window can Granite 4.1 8B use on Tesla P40 24GB?

On Tesla P40 24GB, Granite 4.1 8B can safely use up to 102K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for Tesla P40 24GB See all hardware for Granite 4.1 8B

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<iframe src="https://willitrunai.com/embed/granite-4.1-8b-on-tesla-p40-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

45.0 tok/s

2348 ms

102K

Coding

Runs well

45.0 tok/s

4305 ms

102K

Agentic Coding

Runs well

45.0 tok/s

6262 ms

102K

Reasoning

Runs well

45.0 tok/s

5088 ms

102K

RAG

Runs well

45.0 tok/s

7828 ms

102K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on Tesla P40 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	B69
Q3_K_S	3	3.9 GB	Low	B69
NVFP4	4	4.5 GB	Medium	B69
Q4_K_M	4	4.9 GB	Medium	B70
Q5_K_M	5	5.8 GB	High	A70
Q6_K	6	6.6 GB	High	A71
Q8_0	8	8.6 GB	Very High	A72
F16Best for your GPU	16	16.4 GB	Maximum	A74

Model

Params

Grade

Decode

Capabilities

Qwen3-Coder 30B A3B Instruct

30.5B

30.9 tok/s

Qwen 3.5 27B

27B

13.4 tok/s

Qwen 3.6 27B

27B

13.4 tok/s

Qwen3-VL 30B A3B Instruct

30B

31.9 tok/s

Qwen 3.5 9B

40 tok/s

Frequently asked questions

Can Tesla P40 24GB run Granite 4.1 8B?

Yes, Tesla P40 24GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 45.0 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite 4.1 8B?

The recommended quantization for Granite 4.1 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite 4.1 8B run at on Tesla P40 24GB?

On Tesla P40 24GB, Granite 4.1 8B achieves approximately 45.0 tokens per second decode speed with a time-to-first-token of 4305ms using Q4_K_M quantization.

Can Tesla P40 24GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on Tesla P40 24GB receives a A grade with 45.0 tok/s and 102K context.

What context window can Granite 4.1 8B use on Tesla P40 24GB?

On Tesla P40 24GB, Granite 4.1 8B can safely use up to 102K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.