Can Qwen 2.5 Coder 7B run on RX 6900 XT 16GB?

YES — Runs Great

A71Great

Estimated from fit model

Qwen 2.5 Coder 7B needs ~7.6 GB VRAM. RX 6900 XT 16GB has 16.0 GB. With Q4_K_M quantization, expect ~74 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) — 7.6 GB, 74.2 tok/s, Runs well

7.6 GB required16.0 GB available

48% VRAM used

Fit status

Runs well

Decode

74.2 tok/s

TTFT

2609 ms

Safe context

131K

Memory

7.6 GB / 16.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.9 GB

Runtime0.9 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 7B on RX 6900 XT 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: 74.2 tok/s decode · 2.6s TTFT (warm) · 186 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	A	Runs well	74.2 tok/s	1423 ms	131K
Coding	A	Runs well	74.2 tok/s	2609 ms	131K
Agentic Coding	A	Runs well	74.2 tok/s	3795 ms	131K
Reasoning	A	Runs well	74.2 tok/s	3083 ms	131K
RAG	A	Runs well	74.2 tok/s	4744 ms	131K

Quantization options

How Qwen 2.5 Coder 7B (7B params) fits at each quantization level on RX 6900 XT 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	B67
Q3_K_S	3	3.4 GB	Low	B67
NVFP4	4	3.9 GB	Medium	B68
Q4_K_M	4	4.3 GB	Medium	B68
Q5_K_M	5	5.0 GB	High	B69
Q6_K	6	5.7 GB	High	B69
Q8_0Best for your GPU	8	7.5 GB	Very High	A71
F16	16	14.3 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 2.5 Coder 7B on your machine.

Run

ollama run qwen2.5-coder:7b

Your hardware

More models your RX 6900 XT 16GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	57.1 tok/s
Qwen 3 14B	14B	S	36.9 tok/s
Qwen 3 8B	8B	S	64.3 tok/s
Phi-4-reasoning-plus 14B	14.7B	S	35 tok/s
GPT-OSS 20B	21B	A	33.8 tok/s

Frequently asked questions

Can RX 6900 XT 16GB run Qwen 2.5 Coder 7B?

Yes, RX 6900 XT 16GB can run Qwen 2.5 Coder 7B with a A grade (Runs well). Expected decode speed: 74.2 tok/s.

How much VRAM does Qwen 2.5 Coder 7B need?

Qwen 2.5 Coder 7B (7B parameters) requires approximately 7.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 7B?

The recommended quantization for Qwen 2.5 Coder 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 7B run at on RX 6900 XT 16GB?

On RX 6900 XT 16GB, Qwen 2.5 Coder 7B achieves approximately 74.2 tokens per second decode speed with a time-to-first-token of 2609ms using Q4_K_M quantization.

Can RX 6900 XT 16GB run Qwen 2.5 Coder 7B for coding?

For coding workloads, Qwen 2.5 Coder 7B on RX 6900 XT 16GB receives a A grade with 74.2 tok/s and 131K context.

What context window can Qwen 2.5 Coder 7B use on RX 6900 XT 16GB?

On RX 6900 XT 16GB, Qwen 2.5 Coder 7B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RX 6900 XT 16GB See all hardware for Qwen 2.5 Coder 7B

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<iframe src="https://willitrunai.com/embed/qwen-2.5-coder-7b-on-rx-6900-xt-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

74.2 tok/s

1423 ms

131K

Coding

Runs well

74.2 tok/s

2609 ms

131K

Agentic Coding

Runs well

74.2 tok/s

3795 ms

131K

Reasoning

Runs well

74.2 tok/s

3083 ms

131K

RAG

Runs well

74.2 tok/s

4744 ms

131K

Quantization options

How Qwen 2.5 Coder 7B (7B params) fits at each quantization level on RX 6900 XT 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	B67
Q3_K_S	3	3.4 GB	Low	B67
NVFP4	4	3.9 GB	Medium	B68
Q4_K_M	4	4.3 GB	Medium	B68
Q5_K_M	5	5.0 GB	High	B69
Q6_K	6	5.7 GB	High	B69
Q8_0Best for your GPU	8	7.5 GB	Very High	A71
F16	16	14.3 GB	Maximum	F0

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 9B

57.1 tok/s

Qwen 3 14B

14B

36.9 tok/s

Qwen 3 8B

64.3 tok/s

Phi-4-reasoning-plus 14B

14.7B

35 tok/s

GPT-OSS 20B

21B

33.8 tok/s

Frequently asked questions

Can RX 6900 XT 16GB run Qwen 2.5 Coder 7B?

Yes, RX 6900 XT 16GB can run Qwen 2.5 Coder 7B with a A grade (Runs well). Expected decode speed: 74.2 tok/s.

How much VRAM does Qwen 2.5 Coder 7B need?

Qwen 2.5 Coder 7B (7B parameters) requires approximately 7.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 7B?

The recommended quantization for Qwen 2.5 Coder 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 7B run at on RX 6900 XT 16GB?

On RX 6900 XT 16GB, Qwen 2.5 Coder 7B achieves approximately 74.2 tokens per second decode speed with a time-to-first-token of 2609ms using Q4_K_M quantization.

Can RX 6900 XT 16GB run Qwen 2.5 Coder 7B for coding?

For coding workloads, Qwen 2.5 Coder 7B on RX 6900 XT 16GB receives a A grade with 74.2 tok/s and 131K context.

What context window can Qwen 2.5 Coder 7B use on RX 6900 XT 16GB?

On RX 6900 XT 16GB, Qwen 2.5 Coder 7B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.