Can DeepSeek R1 Distill 8B run on Radeon PRO W7700 16GB?

YES — Runs Great

A70Great

○Estimated from fit model

DeepSeek R1 Distill 8B needs ~9.3 GB VRAM. Radeon PRO W7700 16GB has 16.0 GB. With Q4_K_M quantization, expect ~75 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) — 9.3 GB, 74.9 tok/s, Runs well

9.3 GB required16.0 GB available

58% VRAM used

Fit status

Runs well

Decode

74.9 tok/s

TTFT

2586 ms

Safe context

33K

Memory

9.3 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 8B on Radeon PRO W7700 16GB
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: 74.9 tok/s decode · 2.6s TTFT (warm) · 187 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	74.9 tok/s	1411 ms	33K
Coding	A	Runs well	74.9 tok/s	2586 ms	33K
Agentic Coding	A	Runs well	74.9 tok/s	3762 ms	33K
Reasoning	A	Runs well	74.9 tok/s	3056 ms	33K
RAG	A	Runs well	74.9 tok/s	4702 ms	33K

Quantization options

How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on Radeon PRO W7700 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	B64
Q3_K_S	3	3.9 GB	Low	B64
NVFP4	4	4.5 GB	Medium	B65
Q4_K_M	4	4.9 GB	Medium	B65
Q5_K_M	5	5.8 GB	High	B66
Q6_K	6	6.6 GB	High	B67
Q8_0Best for your GPU	8	8.6 GB	Very High	B68
F16	16	16.4 GB	Maximum	F0

Get started

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

Run

ollama run deepseek-r1:8b

Your hardware

More models your Radeon PRO W7700 16GB can run

Model	Params	Grade	Decode
👁 Alibaba Qwen 3.5 9B	9B	S	66.5 tok/s
👁 Alibaba Qwen 3 14B	14B	S	43 tok/s
👁 Microsoft Phi-4-reasoning-plus 14B	14.7B	S	40.7 tok/s
👁 OpenAI GPT-OSS 20B	21B	A	39.3 tok/s
👁 Mistral Ministral 3 14B	14B	S	42.8 tok/s

Frequently asked questions

See all results for Radeon PRO W7700 16GB See all hardware for DeepSeek R1 Distill 8B

URL: https://willitrunai.com/can-run/deepseek-r1-distill-8b-on-radeon-pro-w7700-16gb

⇱ DeepSeek R1 Distill 8B on Radeon PRO W7700 16GB? YES