Can DeepSeek R1 0528 Qwen3 8B run on Radeon Pro W7800 32GB?

YES — Runs Great

C48Usable
Estimated from fit model

DeepSeek R1 0528 Qwen3 8B needs ~9.9 GB VRAM. Radeon Pro W7800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~70 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
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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) 9.9 GB, 69.6 tok/s, Runs well
9.9 GB required32.0 GB available
31% VRAM used

Fit status

Runs well

Decode

69.6 tok/s

TTFT

2780 ms

Safe context

393K

Memory

9.9 GB / 32.0 GB

Memory breakdown

Weights4.9 GB
KV Cache0.9 GB
Runtime0.9 GB
Headroom3.2 GB

See how fast it feels

See how fast it feelsDeepSeek R1 0528 Qwen3 8B on Radeon Pro W7800 32GB
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: 69.6 tok/s decode · 2.8s TTFT (warm) · 174 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

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well69.6 tok/s1516 ms393K
CodingCRuns well69.6 tok/s2780 ms393K
Agentic CodingCRuns well69.6 tok/s4044 ms393K
ReasoningCRuns well69.6 tok/s3285 ms393K
RAGCRuns well69.6 tok/s5055 ms393K

Quantization options

How DeepSeek R1 0528 Qwen3 8B (8B params) fits at each quantization level on Radeon Pro W7800 32GB (32.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowC43
Q3_K_S
3
3.9 GB
LowC43
NVFP4
4
4.5 GB
MediumC44
Q4_K_M
4
4.9 GB
MediumC44
Q5_K_M
5
5.8 GB
HighC44
Q6_K
6
6.6 GB
HighC44
Q8_0
8
8.6 GB
Very HighC45
F16Best for your GPU
16
16.4 GB
MaximumC49

Get started

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

Run

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

アップグレードオプション

DeepSeek R1 0528 Qwen3 8Bを快適に動かすハードウェア

Frequently asked questions

Can Radeon Pro W7800 32GB run DeepSeek R1 0528 Qwen3 8B?

Yes, Radeon Pro W7800 32GB can run DeepSeek R1 0528 Qwen3 8B with a C grade (Runs well). Expected decode speed: 69.6 tok/s.

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

DeepSeek R1 0528 Qwen3 8B (8B parameters) requires approximately 9.9 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 W7800 32GB?

On Radeon Pro W7800 32GB, DeepSeek R1 0528 Qwen3 8B achieves approximately 69.6 tokens per second decode speed with a time-to-first-token of 2780ms using Q4_K_M quantization.

Can Radeon Pro W7800 32GB run DeepSeek R1 0528 Qwen3 8B for coding?

For coding workloads, DeepSeek R1 0528 Qwen3 8B on Radeon Pro W7800 32GB receives a C grade with 69.6 tok/s and 393K context.

What context window can DeepSeek R1 0528 Qwen3 8B use on Radeon Pro W7800 32GB?

On Radeon Pro W7800 32GB, DeepSeek R1 0528 Qwen3 8B can safely use up to 393K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for Radeon Pro W7800 32GBSee all hardware for DeepSeek R1 0528 Qwen3 8B
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