Can DeepSeek R1 Distill Qwen 14B run on NVIDIA A100 40GB?

YES — Runs Great

C50Usable

○Estimated from fit model

DeepSeek R1 Distill Qwen 14B needs ~15.4 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~153 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) — 15.4 GB, 153.0 tok/s, Runs well

15.4 GB required40.0 GB available

39% VRAM used

Fit status

Runs well

Decode

153.0 tok/s

TTFT

1266 ms

Safe context

256K

Memory

15.4 GB / 40.0 GB

Memory breakdown

Weights8.5 GB

KV Cache1.6 GB

Runtime1.2 GB

Headroom4.0 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill Qwen 14B on NVIDIA A100 40GB
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: 153.0 tok/s decode · 1.3s TTFT (warm) · 382 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	C	Runs well	153.0 tok/s	690 ms	256K
Coding	C	Runs well	153.0 tok/s	1266 ms	256K
Agentic Coding	C	Runs well	153.0 tok/s	1841 ms	256K
Reasoning	C	Runs well	153.0 tok/s	1496 ms	256K
RAG	C	Runs well	153.0 tok/s	2301 ms	256K

Quantization options

How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	C43
Q3_K_S	3	6.9 GB	Low	C43
NVFP4	4	7.8 GB	Medium	C43
Q4_K_M	4	8.5 GB	Medium	C44
Q5_K_M	5	10.1 GB	High	C44
Q6_K	6	11.5 GB	High	C45
Q8_0	8	15.0 GB	Very High	C46
F16Best for your GPU	16	28.7 GB	Maximum	C48

Get started

Copy-paste commands to run DeepSeek R1 Distill Qwen 14B on your machine.

Run

lms load hf-unsloth--deepseek-r1-distill-qwen-14b-gguf && lms server start

Frequently asked questions

See all results for NVIDIA A100 40GB See all hardware for DeepSeek R1 Distill Qwen 14B

URL: https://willitrunai.com/can-run/hf-unsloth--deepseek-r1-distill-qwen-14b-gguf-on-a100-40gb

⇱ DeepSeek R1 Distill Qwen 14B on NVIDIA A100 40GB? YES