Can DeepSeek R1 Distill Qwen 14B run on RTX 3090 24GB?

YES — Runs Great

C54Usable

○Estimated from fit model

DeepSeek R1 Distill Qwen 14B needs ~13.8 GB VRAM. RTX 3090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~77 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) — 13.8 GB, 76.7 tok/s, Runs well

13.8 GB required24.0 GB available

58% VRAM used

Fit status

Runs well

Decode

76.7 tok/s

TTFT

2523 ms

Safe context

116K

Memory

13.8 GB / 24.0 GB

Memory breakdown

Weights8.5 GB

KV Cache1.6 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill Qwen 14B on RTX 3090 24GB
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: 76.7 tok/s decode · 2.5s TTFT (warm) · 192 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	76.7 tok/s	1376 ms	116K
Coding	C	Runs well	76.7 tok/s	2523 ms	116K
Agentic Coding	B	Runs well	76.7 tok/s	3670 ms	116K
Reasoning	C	Runs well	76.7 tok/s	2982 ms	116K
RAG	B	Runs well	76.7 tok/s	4588 ms	116K

Quantization options

How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on RTX 3090 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	C46
Q3_K_S	3	6.9 GB	Low	C47
NVFP4	4	7.8 GB	Medium	C47
Q4_K_M	4	8.5 GB	Medium	C48
Q5_K_M	5	10.1 GB	High	C49
Q6_K	6	11.5 GB	High	C50
Q8_0Best for your GPU	8	15.0 GB	Very High	C50
F16	16	28.7 GB	Maximum	F0

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 RTX 3090 24GB See all hardware for DeepSeek R1 Distill Qwen 14B

URL: https://willitrunai.com/can-run/hf-unsloth--deepseek-r1-distill-qwen-14b-gguf-on-rtx-3090-24gb

⇱ DeepSeek R1 Distill Qwen 14B on RTX 3090 24GB? YES