Can DeepSeek R1 0528 Qwen3 8B run on Radeon Pro W7500 8GB?

Q: What should I upgrade first if DeepSeek R1 0528 Qwen3 8B feels slow on Radeon Pro W7500 8GB?

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

YES — Tight Fit

C50Usable

Estimated from fit model

DeepSeek R1 0528 Qwen3 8B needs ~7.5 GB VRAM. Radeon Pro W7500 8GB has 8.0 GB. With Q4_K_M quantization, expect ~27 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth

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) — 7.5 GB, 27.1 tok/s, Tight fit

7.5 GB required8.0 GB available

94% VRAM used

Fit status

Tight fit

Decode

27.1 tok/s

TTFT

7149 ms

Safe context

24K

Memory

7.5 GB / 8.0 GB

Memory breakdown

Weights4.9 GB

KV Cache0.9 GB

Runtime0.9 GB

Headroom0.8 GB

See how fast it feels

See how fast it feelsDeepSeek R1 0528 Qwen3 8B on Radeon Pro W7500 8GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 27.1 tok/s decode · 7.1s TTFT (warm) · 68 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	C	Tight fit	27.1 tok/s	3899 ms	24K
Coding	C	Tight fit	27.1 tok/s	7149 ms	24K
Agentic Coding	D	Runs with offload (needs ~0.3 GB host RAM)	18.1 tok/s	15576 ms	24K
Reasoning	C	Tight fit	27.1 tok/s	8448 ms	24K
RAG	D	Runs with offload (needs ~0.3 GB host RAM)	18.1 tok/s	19470 ms

Quantization options

How DeepSeek R1 0528 Qwen3 8B (8B params) fits at each quantization level on Radeon Pro W7500 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	C54
Q3_K_S	3	3.9 GB	Low	C53
NVFP4	4

Get started

Copy-paste commands to run DeepSeek R1 0528 Qwen3 8B on your machine.

Run

lms load hf-lmstudio-community--deepseek-r1-0528-qwen3-8b-gguf && lms server start

Upgrade options

Hardware that runs DeepSeek R1 0528 Qwen3 8B well

RX 9060 XT 16GBBudget pick

16 GB VRAM (+8)320 GB/s (+96)

Raises estimated decode speed by about 52%.41.3 tok/s decode

Raises estimated decode speed by about 52%.

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

~$349 MSRP

RX 7700 XT 12GBBest value

12 GB VRAM (+4)432 GB/s (+208)

Raises estimated decode speed by about 96%.53.1 tok/s decode

Raises estimated decode speed by about 96%.

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

~$449 MSRP

RX 6700 XT 12GBAMD upgrade

12 GB VRAM (+4)384 GB/s (+160)

Raises estimated decode speed by about 51%.40.9 tok/s decode

Raises estimated decode speed by about 51%.

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

~$479 MSRP

Frequently asked questions

Can Radeon Pro W7500 8GB run DeepSeek R1 0528 Qwen3 8B?

Yes, Radeon Pro W7500 8GB can run DeepSeek R1 0528 Qwen3 8B with a C grade (Tight fit). Expected decode speed: 27.1 tok/s.

How much VRAM does DeepSeek R1 0528 Qwen3 8B need?

DeepSeek R1 0528 Qwen3 8B (8B parameters) requires approximately 7.5 GB of memory with Q4_K_M quantization.

What is the best quantization for DeepSeek R1 0528 Qwen3 8B?

The recommended quantization for DeepSeek R1 0528 Qwen3 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will DeepSeek R1 0528 Qwen3 8B run at on Radeon Pro W7500 8GB?

On Radeon Pro W7500 8GB, DeepSeek R1 0528 Qwen3 8B achieves approximately 27.1 tokens per second decode speed with a time-to-first-token of 7149ms using Q4_K_M quantization.

Can Radeon Pro W7500 8GB run DeepSeek R1 0528 Qwen3 8B for coding?

For coding workloads, DeepSeek R1 0528 Qwen3 8B on Radeon Pro W7500 8GB receives a C grade with 27.1 tok/s and 24K context.

What context window can DeepSeek R1 0528 Qwen3 8B use on Radeon Pro W7500 8GB?

On Radeon Pro W7500 8GB, DeepSeek R1 0528 Qwen3 8B can safely use up to 24K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for Radeon Pro W7500 8GB See all hardware for DeepSeek R1 0528 Qwen3 8B

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