Can Granite Code 3B run on GTX 1060 6GB?

Q: What should I upgrade first if Granite Code 3B feels slow on GTX 1060 6GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

YES — With Offload

B67Good

Estimated from fit model

Granite Code 3B needs ~6.1 GB VRAM. GTX 1060 6GB has 6.0 GB. With Q4_K_M quantization, expect ~42 tok/s.

Runtime: OllamaCapacity: OffloadBandwidth: Very lowStack: BasicBottleneck: Host offload

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) — 6.1 GB, 42.0 tok/s, Runs with offload (needs ~0 GB host RAM)

6.1 GB required6.0 GB available

102% VRAM needed

100 MB over capacity — needs offload or smaller quantization

Fit status

Runs with offload (needs ~0 GB host RAM)

Decode

42.0 tok/s

TTFT

4610 ms

Safe context

Memory

6.1 GB / 6.0 GB

Memory breakdown

Weights1.8 GB

KV Cache2.5 GB

Runtime1.2 GB

Headroom0.6 GB

See how fast it feels

See how fast it feelsGranite Code 3B on GTX 1060 6GB
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: 42.0 tok/s decode · 4.6s TTFT (warm) · 105 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

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

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	42.0 tok/s	2514 ms	8K
Coding	B	Runs with offload	42.0 tok/s	4610 ms	8K
Agentic Coding	F	Too heavy	20.6 tok/s	13658 ms	8K
Reasoning	B	Runs with offload	42.0 tok/s	5448 ms	8K
RAG	F	Too heavy	20.6 tok/s	17073 ms	8K

Quantization options

How Granite Code 3B (3B params) fits at each quantization level on GTX 1060 6GB (6.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.2 GB	Low	B69
Q3_K_S	3	1.5 GB	Low	A70
NVFP4	4

Get started

Copy-paste commands to run Granite Code 3B on your machine.

Run

ollama run granite-code:3b

Upgrade options

Hardware that runs Granite Code 3B well

RTX 3050 8GBBudget pick

8 GB VRAM (+2)224 GB/s (+32)

Adds memory headroom for longer context windows and future model growth.42 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$249 MSRP

RTX 4060 8GBBest value

8 GB VRAM (+2)272 GB/s (+80)

Adds memory headroom for longer context windows and future model growth.42 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$299 MSRP

RTX 5060 8GBNVIDIA upgrade

8 GB VRAM (+2)448 GB/s (+256)

Adds memory headroom for longer context windows and future model growth.42 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$299 MSRP

Frequently asked questions

Can GTX 1060 6GB run Granite Code 3B?

Yes, GTX 1060 6GB can run Granite Code 3B with a B grade (Runs with offload). Expected decode speed: 42.0 tok/s.

How much VRAM does Granite Code 3B need?

Granite Code 3B (3B parameters) requires approximately 6.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 3B?

The recommended quantization for Granite Code 3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 3B run at on GTX 1060 6GB?

On GTX 1060 6GB, Granite Code 3B achieves approximately 42.0 tokens per second decode speed with a time-to-first-token of 4610ms using Q4_K_M quantization.

Can GTX 1060 6GB run Granite Code 3B for coding?

For coding workloads, Granite Code 3B on GTX 1060 6GB receives a B grade with 42.0 tok/s and 8K context.

What context window can Granite Code 3B use on GTX 1060 6GB?

On GTX 1060 6GB, Granite Code 3B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

What should I upgrade first if Granite Code 3B feels slow on GTX 1060 6GB?

See all results for GTX 1060 6GB See all hardware for Granite Code 3B

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