Can Qwen 2.5 Coder 14B run on RX 7900 XTX 24GB?

YES — Runs Great

B69Good

Estimated from fit model

Qwen 2.5 Coder 14B needs ~14.8 GB VRAM. RX 7900 XTX 24GB has 24.0 GB. With Q4_K_M quantization, expect ~87 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 14.8 GB, 87.4 tok/s, Runs well

14.8 GB required24.0 GB available

62% VRAM used

Fit status

Runs well

Decode

87.4 tok/s

TTFT

2215 ms

Safe context

66K

Memory

14.8 GB / 24.0 GB

Memory breakdown

Weights8.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 14B on RX 7900 XTX 24GB
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: 87.4 tok/s decode · 2.2s TTFT (warm) · 219 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	87.4 tok/s	1208 ms	66K
Coding	B	Runs well	87.4 tok/s	2215 ms	66K
Agentic Coding	A	Runs well	87.4 tok/s	3222 ms	66K
Reasoning	B	Runs well	80.9 tok/s	2827 ms	66K
RAG	A	Runs well	87.4 tok/s	4027 ms	66K

Quantization options

How Qwen 2.5 Coder 14B (14B params) fits at each quantization level on RX 7900 XTX 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	B60
Q3_K_S	3	6.9 GB	Low	B61
NVFP4	4

Get started

Copy-paste commands to run Qwen 2.5 Coder 14B on your machine.

Run

ollama run qwen2.5-coder:14b

Frequently asked questions

Can RX 7900 XTX 24GB run Qwen 2.5 Coder 14B?

Yes, RX 7900 XTX 24GB can run Qwen 2.5 Coder 14B with a B grade (Runs well). Expected decode speed: 87.4 tok/s.

How much VRAM does Qwen 2.5 Coder 14B need?

Qwen 2.5 Coder 14B (14B parameters) requires approximately 14.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 14B?

The recommended quantization for Qwen 2.5 Coder 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 14B run at on RX 7900 XTX 24GB?

On RX 7900 XTX 24GB, Qwen 2.5 Coder 14B achieves approximately 87.4 tokens per second decode speed with a time-to-first-token of 2215ms using Q4_K_M quantization.

Can RX 7900 XTX 24GB run Qwen 2.5 Coder 14B for coding?

For coding workloads, Qwen 2.5 Coder 14B on RX 7900 XTX 24GB receives a B grade with 87.4 tok/s and 66K context.

What context window can Qwen 2.5 Coder 14B use on RX 7900 XTX 24GB?

On RX 7900 XTX 24GB, Qwen 2.5 Coder 14B can safely use up to 66K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RX 7900 XTX 24GB See all hardware for Qwen 2.5 Coder 14B

Embed this result▼

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

<iframe src="https://willitrunai.com/embed/qwen-2.5-coder-14b-on-rx-7900-xtx-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: