Can Granite 4.1 8B run on NVIDIA T4 16GB?

YES — Runs Great

A77Great

Estimated from fit model

Granite 4.1 8B needs ~10.1 GB VRAM. NVIDIA T4 16GB has 16.0 GB. With Q4_K_M quantization, expect ~46 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) — 10.1 GB, 45.8 tok/s, Runs well

10.1 GB required16.0 GB available

63% VRAM used

Fit status

Runs well

Decode

45.8 tok/s

TTFT

4225 ms

Safe context

55K

Memory

10.1 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGranite 4.1 8B on NVIDIA T4 16GB
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: 45.8 tok/s decode · 4.2s TTFT (warm) · 115 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	45.8 tok/s	2305 ms	55K
Coding	A	Runs well	45.8 tok/s	4225 ms	55K
Agentic Coding	A	Runs well	45.8 tok/s	6146 ms	55K
Reasoning	A	Runs well	45.8 tok/s	4993 ms	55K
RAG	A	Runs well	45.8 tok/s	7682 ms	55K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on NVIDIA T4 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	A71
Q3_K_S	3	3.9 GB	Low	A72
NVFP4	4	4.5 GB	Medium	A73
Q4_K_M	4	4.9 GB	Medium	A73
Q5_K_M	5	5.8 GB	High	A74
Q6_K	6	6.6 GB	High	A75
Q8_0Best for your GPU	8	8.6 GB	Very High	A76
F16	16	16.4 GB	Maximum	F0

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 NVIDIA T4 16GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	40.7 tok/s
Qwen 3 14B	14B	S	26.3 tok/s
Phi-4-reasoning-plus 14B	14.7B	S	24.9 tok/s
GPT-OSS 20B	21B	A	22.3 tok/s
Ministral 3 14B	14B	A	26.2 tok/s

Frequently asked questions

Can NVIDIA T4 16GB run Granite 4.1 8B?

Yes, NVIDIA T4 16GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 45.8 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.1 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 NVIDIA T4 16GB?

On NVIDIA T4 16GB, Granite 4.1 8B achieves approximately 45.8 tokens per second decode speed with a time-to-first-token of 4225ms using Q4_K_M quantization.

Can NVIDIA T4 16GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on NVIDIA T4 16GB receives a A grade with 45.8 tok/s and 55K context.

What context window can Granite 4.1 8B use on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Granite 4.1 8B can safely use up to 55K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for NVIDIA T4 16GB See all hardware for Granite 4.1 8B

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/granite-4.1-8b-on-t4-16gb" 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

45.8 tok/s

2305 ms

55K

Coding

Runs well

45.8 tok/s

4225 ms

55K

Agentic Coding

Runs well

45.8 tok/s

6146 ms

55K

Reasoning

Runs well

45.8 tok/s

4993 ms

55K

RAG

Runs well

45.8 tok/s

7682 ms

55K

Quant

Bits

VRAM

Quality

Fit

Q2_K

3.1 GB

Low

A71

Q3_K_S

3.9 GB

Low

A72

NVFP4

4.5 GB

Medium

A73

Q4_K_M

4.9 GB

Medium

A73

Q5_K_M

5.8 GB

High

A74

Q6_K

6.6 GB

High

A75

Q8_0Best for your GPU

8.6 GB

Very High

A76

F16

16.4 GB

Maximum

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 9B

40.7 tok/s

Qwen 3 14B

14B

26.3 tok/s

Phi-4-reasoning-plus 14B

14.7B

24.9 tok/s

GPT-OSS 20B

21B

22.3 tok/s

Ministral 3 14B

14B

26.2 tok/s

Frequently asked questions

Can NVIDIA T4 16GB run Granite 4.1 8B?

Yes, NVIDIA T4 16GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 45.8 tok/s.

How much VRAM does Granite 4.1 8B need?

Granite 4.1 8B (8B parameters) requires approximately 10.1 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 NVIDIA T4 16GB?

On NVIDIA T4 16GB, Granite 4.1 8B achieves approximately 45.8 tokens per second decode speed with a time-to-first-token of 4225ms using Q4_K_M quantization.

Can NVIDIA T4 16GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on NVIDIA T4 16GB receives a A grade with 45.8 tok/s and 55K context.

What context window can Granite 4.1 8B use on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Granite 4.1 8B can safely use up to 55K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.