Can Qwen 3 14B run on RTX 5090 Laptop 24GB?

YES — Runs Great

S96Excellent

Estimated from fit model

Qwen 3 14B needs ~14.6 GB VRAM. RTX 5090 Laptop 24GB has 24.0 GB. With Q4_K_M quantization, expect ~95 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) — 14.6 GB, 95.2 tok/s, Runs well

14.6 GB required24.0 GB available

61% VRAM used

Fit status

Runs well

Decode

95.2 tok/s

TTFT

2034 ms

Safe context

78K

Memory

14.6 GB / 24.0 GB

Memory breakdown

Weights8.5 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsQwen 3 14B on RTX 5090 Laptop 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: 95.2 tok/s decode · 2.0s TTFT (warm) · 238 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	S	Runs well	95.2 tok/s	1109 ms	78K
Coding	S	Runs well	95.2 tok/s	2034 ms	78K
Agentic Coding	S	Runs well	95.2 tok/s	2959 ms	78K
Reasoning	S	Runs well	95.2 tok/s	2404 ms	78K
RAG	S	Runs well	95.2 tok/s	3698 ms	78K

Quantization options

How Qwen 3 14B (14B params) fits at each quantization level on RTX 5090 Laptop 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	S86
Q3_K_S	3	6.9 GB	Low	S87
NVFP4	4

Get started

Copy-paste commands to run Qwen 3 14B on your machine.

Run

ollama run qwen3

Your hardware

More models your RTX 5090 Laptop 24GB can run

Model	Params	Grade	Decode	Capabilities
Qwen3-Coder 30B A3B Instruct	30.5B	S	113.8 tok/s
Qwen 3.5 27B	27B	S	49.4 tok/s

Frequently asked questions

Can RTX 5090 Laptop 24GB run Qwen 3 14B?

Yes, RTX 5090 Laptop 24GB can run Qwen 3 14B with a S grade (Runs well). Expected decode speed: 95.2 tok/s.

How much VRAM does Qwen 3 14B need?

Qwen 3 14B (14B parameters) requires approximately 14.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 14B?

The recommended quantization for Qwen 3 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 14B run at on RTX 5090 Laptop 24GB?

On RTX 5090 Laptop 24GB, Qwen 3 14B achieves approximately 95.2 tokens per second decode speed with a time-to-first-token of 2034ms using Q4_K_M quantization.

Can RTX 5090 Laptop 24GB run Qwen 3 14B for coding?

For coding workloads, Qwen 3 14B on RTX 5090 Laptop 24GB receives a S grade with 95.2 tok/s and 78K context.

What context window can Qwen 3 14B use on RTX 5090 Laptop 24GB?

On RTX 5090 Laptop 24GB, Qwen 3 14B can safely use up to 78K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX 5090 Laptop 24GB See all hardware for Qwen 3 14B

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/qwen-3-14b-on-rtx-5090-laptop-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: