Will It Run AI

Can Granite 4.1 8B run on RTX 4060 Ti 16GB?

YES — Runs Great

A77Great
Estimated from fit model

Granite 4.1 8B needs ~10.1 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~46 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: 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) 10.1 GB, 46.3 tok/s, Runs well
10.1 GB required16.0 GB available
63% VRAM used

Fit status

Runs well

Decode

46.3 tok/s

TTFT

4180 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 RTX 4060 Ti 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: 46.3 tok/s decode · 4.2s TTFT (warm) · 116 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 well46.3 tok/s2280 ms55K
CodingARuns well46.3 tok/s4180 ms55K
Agentic CodingARuns well46.3 tok/s6080 ms55K
ReasoningARuns well46.3 tok/s4940 ms55K
RAGARuns well46.3 tok/s7600 ms55K

Quantization options

How Granite 4.1 8B (8B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowA71
Q3_K_S
3
3.9 GB
LowA72
NVFP4
4
4.5 GB
MediumA73
Q4_K_M
4
4.9 GB
MediumA73
Q5_K_M
5
5.8 GB
HighA74
Q6_K
6
6.6 GB
HighA75
Q8_0Best for your GPU
8
8.6 GB
Very HighA76
F16
16
16.4 GB
MaximumF0

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 RTX 4060 Ti 16GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3.5 9B9BS41.2 tok/s
AlibabaQwen 3 14B14BS26.6 tok/s
MicrosoftPhi-4-reasoning-plus 14B14.7BS25.2 tok/s
OpenAIGPT-OSS 20B21BA23.5 tok/s
MistralMinistral 3 14B14BA26.5 tok/s

Frequently asked questions

Can RTX 4060 Ti 16GB run Granite 4.1 8B?

Yes, RTX 4060 Ti 16GB can run Granite 4.1 8B with a A grade (Runs well). Expected decode speed: 46.3 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 RTX 4060 Ti 16GB?

On RTX 4060 Ti 16GB, Granite 4.1 8B achieves approximately 46.3 tokens per second decode speed with a time-to-first-token of 4180ms using Q4_K_M quantization.

Can RTX 4060 Ti 16GB run Granite 4.1 8B for coding?

For coding workloads, Granite 4.1 8B on RTX 4060 Ti 16GB receives a A grade with 46.3 tok/s and 55K context.

What context window can Granite 4.1 8B use on RTX 4060 Ti 16GB?

On RTX 4060 Ti 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 RTX 4060 Ti 16GBSee all hardware for Granite 4.1 8B
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