Will It Run AI

Can Qwen 2.5 Coder 0.5B run on Radeon Pro W7500 8GB?

YES — Runs Great

C49Usable
Estimated from fit model

Qwen 2.5 Coder 0.5B needs ~2.2 GB VRAM. Radeon Pro W7500 8GB has 8.0 GB. With Q4_K_M quantization, expect ~7 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
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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) 2.2 GB, 7.0 tok/s, Runs well
2.2 GB required8.0 GB available
28% VRAM used

Fit status

Runs well

Decode

7.0 tok/s

TTFT

27657 ms

Safe context

131K

Memory

2.2 GB / 8.0 GB

Memory breakdown

Weights0.3 GB
KV Cache0.2 GB
Runtime0.9 GB
Headroom0.8 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 0.5B on Radeon Pro W7500 8GB
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: 7.0 tok/s decode · 27.7s TTFT (warm) · 18 tok/s prefill

What limits this setup

This model fits, but memory bandwidth is the part holding decode speed back.

Throughput will feel slow

Estimated decode speed is only 7.0 tok/s, so this is more of a technical fit than a comfortable daily-driver setup.

Best improvement path

Prioritize bandwidth, not only capacity

If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well7.0 tok/s15086 ms131K
CodingCRuns well7.0 tok/s27657 ms131K
Agentic CodingCRuns well7.0 tok/s40229 ms131K
ReasoningCRuns well7.0 tok/s32686 ms131K
RAGCRuns well7.0 tok/s50286 ms131K

Quantization options

How Qwen 2.5 Coder 0.5B (0.5B params) fits at each quantization level on Radeon Pro W7500 8GB (8.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
0.2 GB
LowB58
Q3_K_S
3
0.2 GB
LowB58
NVFP4
4
0.3 GB
MediumB58
Q4_K_M
4
0.3 GB
MediumB58
Q5_K_M
5
0.4 GB
HighB58
Q6_K
6
0.4 GB
HighB58
Q8_0
8
0.5 GB
Very HighB58
F16Best for your GPU
16
1.0 GB
MaximumB59

Get started

Copy-paste commands to run Qwen 2.5 Coder 0.5B on your machine.

Run

ollama run qwen2.5-coder:0.5b

Frequently asked questions

Can Radeon Pro W7500 8GB run Qwen 2.5 Coder 0.5B?

Yes, Radeon Pro W7500 8GB can run Qwen 2.5 Coder 0.5B with a C grade (Runs well). Expected decode speed: 7.0 tok/s.

How much VRAM does Qwen 2.5 Coder 0.5B need?

Qwen 2.5 Coder 0.5B (0.5B parameters) requires approximately 2.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 0.5B?

The recommended quantization for Qwen 2.5 Coder 0.5B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 0.5B run at on Radeon Pro W7500 8GB?

On Radeon Pro W7500 8GB, Qwen 2.5 Coder 0.5B achieves approximately 7.0 tokens per second decode speed with a time-to-first-token of 27657ms using Q4_K_M quantization.

Can Radeon Pro W7500 8GB run Qwen 2.5 Coder 0.5B for coding?

For coding workloads, Qwen 2.5 Coder 0.5B on Radeon Pro W7500 8GB receives a C grade with 7.0 tok/s and 131K context.

What context window can Qwen 2.5 Coder 0.5B use on Radeon Pro W7500 8GB?

On Radeon Pro W7500 8GB, Qwen 2.5 Coder 0.5B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

What should I upgrade first if Qwen 2.5 Coder 0.5B feels slow on Radeon Pro W7500 8GB?

Prioritize bandwidth, not only capacity. If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.

See all results for Radeon Pro W7500 8GBSee all hardware for Qwen 2.5 Coder 0.5B
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