Can DeepSeek R1 Distill 14B run on RTX 5070 Ti 16GB?

YES — Tight Fit

A78Great

○Estimated from fit model

DeepSeek R1 Distill 14B needs ~14.3 GB VRAM. RTX 5070 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~73 tok/s.

Runtime: OllamaCapacity: TightBandwidth: 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) — 14.3 GB, 72.5 tok/s, Tight fit

14.3 GB required16.0 GB available

89% VRAM used

Fit status

Tight fit

Decode

72.5 tok/s

TTFT

2670 ms

Safe context

25K

Memory

14.3 GB / 16.0 GB

Memory breakdown

Weights8.5 GB

KV Cache2.9 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsDeepSeek R1 Distill 14B on RTX 5070 Ti 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: 72.5 tok/s decode · 2.7s TTFT (warm) · 181 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	A	Runs well	72.5 tok/s	1456 ms	25K
Coding	A	Tight fit	72.5 tok/s	2670 ms	25K
Agentic Coding	B	Runs with offload (needs ~0.6 GB host RAM)	47.9 tok/s	5885 ms	25K
Reasoning	A	Tight fit	72.5 tok/s	3155 ms	25K
RAG	B	Runs with offload (needs ~0.6 GB host RAM)	47.9 tok/s	7356 ms	25K

Quantization options

How DeepSeek R1 Distill 14B (14B params) fits at each quantization level on RTX 5070 Ti 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	A74
Q3_K_S	3	6.9 GB	Low	A75
NVFP4	4	7.8 GB	Medium	A76
Q4_K_M	4	8.5 GB	Medium	A76
Q5_K_M	5	10.1 GB	High	A76
Q6_KBest for your GPU	6	11.5 GB	High	A75
Q8_0	8	15.0 GB	Very High	F0
F16	16	28.7 GB	Maximum	F0

Get started

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

Run

ollama run deepseek-r1

Your hardware

More models your RTX 5070 Ti 16GB can run

Model	Params	Grade	Decode
👁 Microsoft Phi-4-reasoning-plus 14B	14.7B	S	68.7 tok/s
👁 OpenAI GPT-OSS 20B	21B	A	65.8 tok/s
👁 Mistral Codestral 2 25.08	22B	A	25.7 tok/s
👁 Tsinghua/Zhipu CogVLM2 19B	19B	A	36.7 tok/s
👁 IBM Granite Code 20B	20B	B	29.9 tok/s

Frequently asked questions

See all results for RTX 5070 Ti 16GB See all hardware for DeepSeek R1 Distill 14B

URL: https://willitrunai.com/can-run/deepseek-r1-distill-14b-on-rtx-5070-ti-16gb

⇱ DeepSeek R1 Distill 14B on RTX 5070 Ti 16GB? TIGHT FIT