Can Granite 3.1 8B run on RTX 4070 Super 12GB?

YES — Runs Great

B61Good

○Estimated from fit model

Granite 3.1 8B needs ~8.9 GB VRAM. RTX 4070 Super 12GB has 12.0 GB. With Q4_K_M quantization, expect ~98 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: 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) — 8.9 GB, 98.3 tok/s, Runs well

8.9 GB required12.0 GB available

74% VRAM used

Fit status

Runs well

Decode

98.3 tok/s

TTFT

1969 ms

Safe context

41K

Memory

8.9 GB / 12.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.2 GB

See how fast it feels

See how fast it feelsGranite 3.1 8B on RTX 4070 Super 12GB
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: 98.3 tok/s decode · 2.0s TTFT (warm) · 246 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	B	Runs well	98.3 tok/s	1074 ms	41K
Coding	B	Runs well	98.3 tok/s	1969 ms	41K
Agentic Coding	B	Tight fit	98.3 tok/s	2864 ms	41K
Reasoning	B	Runs well	98.3 tok/s	2327 ms	41K
RAG	B	Tight fit	98.3 tok/s	3580 ms	41K

Quantization options

How Granite 3.1 8B (8B params) fits at each quantization level on RTX 4070 Super 12GB (12.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C54
Q3_K_S	3	3.9 GB	Low	B55
NVFP4	4	4.5 GB	Medium	B56
Q4_K_M	4	4.9 GB	Medium	B56
Q5_K_M	5	5.8 GB	High	B57
Q6_K	6	6.6 GB	High	B57
Q8_0Best for your GPU	8	8.6 GB	Very High	B56
F16	16	16.4 GB	Maximum	F0

Get started

Copy-paste commands to run Granite 3.1 8B on your machine.

Run

ollama run granite3.1-dense

Frequently asked questions

See all results for RTX 4070 Super 12GB See all hardware for Granite 3.1 8B

URL: https://willitrunai.com/can-run/granite-3.1-8b-on-rtx-4070-super-12gb

⇱ Granite 3.1 8B on RTX 4070 Super 12GB? YES