Can Granite Code 3B run on RX 5600 XT 6GB?

YES — With Offload

B67Good

Estimated from fit model

Granite Code 3B needs ~5.8 GB VRAM. RX 5600 XT 6GB has 6.0 GB. With Q4_K_M quantization, expect ~42 tok/s.

Runtime: llama.cppCapacity: OffloadBandwidth: LowStack: 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) — 5.8 GB, 42.0 tok/s, Runs with offload

5.8 GB required6.0 GB available

97% VRAM used

Fit status

Runs with offload

Decode

42.0 tok/s

TTFT

4610 ms

Safe context

Memory

5.8 GB / 6.0 GB

Memory breakdown

Weights1.8 GB

KV Cache2.5 GB

Runtime0.9 GB

Headroom0.6 GB

See how fast it feels

See how fast it feelsGranite Code 3B on RX 5600 XT 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.

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	31.2 tok/s	9024 ms	8K
Reasoning	B	Runs with offload	42.0 tok/s	5448 ms	8K
RAG	F	Too heavy	31.2 tok/s	11280 ms	8K

Quantization options

How Granite Code 3B (3B params) fits at each quantization level on RX 5600 XT 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	1.7 GB	Medium	A71
Q4_K_M	4	1.8 GB	Medium	A71
Q5_K_M	5	2.2 GB	High	A71
Q6_K	6	2.5 GB	High	A70
Q8_0Best for your GPU	8	3.2 GB	Very High	B70
F16	16	6.1 GB	Maximum	F0

Get started

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

Run

ollama run granite-code:3b

Upgrade-Optionen

Hardware, die Granite Code 3B gut ausführt

RX 580 8GBGünstige Wahl

8 GB VRAM (+2)

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

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

ca. $229 MSRP

RX 9060 8GBBestes Preis-Leistungs-Verhältnis

8 GB VRAM (+2)

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

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

ca. $249 MSRP

RX 7600 8GBAMD-Upgrade

8 GB VRAM (+2)

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

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

ca. $269 MSRP

Frequently asked questions

Can RX 5600 XT 6GB run Granite Code 3B?

Yes, RX 5600 XT 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 5.8 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 RX 5600 XT 6GB?

On RX 5600 XT 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 RX 5600 XT 6GB run Granite Code 3B for coding?

For coding workloads, Granite Code 3B on RX 5600 XT 6GB receives a B grade with 42.0 tok/s and 8K context.

What context window can Granite Code 3B use on RX 5600 XT 6GB?

On RX 5600 XT 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 RX 5600 XT 6GB?

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

See all results for RX 5600 XT 6GB See all hardware for Granite Code 3B

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