Can Qwen 2.5 14B run on RTX 3090 24GB?

YES — Runs Great

S86Excellent

Estimated from fit model

Qwen 2.5 14B needs ~15.1 GB VRAM. RTX 3090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~83 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) — 15.1 GB, 82.9 tok/s, Runs well

15.1 GB required24.0 GB available

63% VRAM used

Fit status

Runs well

Decode

82.9 tok/s

TTFT

2336 ms

Safe context

65K

Memory

15.1 GB / 24.0 GB

Memory breakdown

Weights8.5 GB

KV Cache2.9 GB

Runtime1.2 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsQwen 2.5 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: 82.9 tok/s decode · 2.3s TTFT (warm) · 207 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	82.9 tok/s	1274 ms	65K
Coding	S	Runs well	82.9 tok/s	2336 ms	65K
Agentic Coding	S	Runs well	82.9 tok/s	3399 ms	65K
Reasoning	S	Runs well	82.9 tok/s	2761 ms	65K
RAG	S	Runs well	82.9 tok/s	4248 ms	65K

Quantization options

How Qwen 2.5 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	A77
Q3_K_S	3	6.9 GB	Low	A77
NVFP4	4	7.8 GB	Medium	A78
Q4_K_M	4	8.5 GB	Medium	A78
Q5_K_M	5	10.1 GB	High	A79
Q6_K	6	11.5 GB	High	A80
Q8_0Best for your GPU	8	15.0 GB	Very High	A81
F16	16	28.7 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 2.5 14B on your machine.

Run

ollama run qwen2.5

Your hardware

More models your RTX 3090 24GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	99.1 tok/s
Qwen 3.5 27B	27B	S	43 tok/s
Qwen 3.6 27B	27B	S	43.1 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	102.5 tok/s
Qwen 3.5 35B A3B	35B	A	55.5 tok/s

Frequently asked questions

Can RTX 3090 24GB run Qwen 2.5 14B?

Yes, RTX 3090 24GB can run Qwen 2.5 14B with a S grade (Runs well). Expected decode speed: 82.9 tok/s.

How much VRAM does Qwen 2.5 14B need?

Qwen 2.5 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 14B?

The recommended quantization for Qwen 2.5 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 14B run at on RTX 3090 24GB?

On RTX 3090 24GB, Qwen 2.5 14B achieves approximately 82.9 tokens per second decode speed with a time-to-first-token of 2336ms using Q4_K_M quantization.

Can RTX 3090 24GB run Qwen 2.5 14B for coding?

For coding workloads, Qwen 2.5 14B on RTX 3090 24GB receives a S grade with 82.9 tok/s and 65K context.

What context window can Qwen 2.5 14B use on RTX 3090 24GB?

On RTX 3090 24GB, Qwen 2.5 14B can safely use up to 65K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX 3090 24GB See all hardware for Qwen 2.5 14B

Embed this result▼

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<iframe src="https://willitrunai.com/embed/qwen-2.5-14b-on-rtx-3090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

82.9 tok/s

1274 ms

65K

Coding

Runs well

82.9 tok/s

2336 ms

65K

Agentic Coding

Runs well

82.9 tok/s

3399 ms

65K

Reasoning

Runs well

82.9 tok/s

2761 ms

65K

RAG

Runs well

82.9 tok/s

4248 ms

65K

Quantization options

How Qwen 2.5 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	A77
Q3_K_S	3	6.9 GB	Low	A77
NVFP4	4	7.8 GB	Medium	A78
Q4_K_M	4	8.5 GB	Medium	A78
Q5_K_M	5	10.1 GB	High	A79
Q6_K	6	11.5 GB	High	A80
Q8_0Best for your GPU	8	15.0 GB	Very High	A81
F16	16	28.7 GB	Maximum	F0

Model

Params

Grade

Decode

Capabilities

Qwen3-Coder 30B A3B Instruct

30.5B

99.1 tok/s

Qwen 3.5 27B

27B

43 tok/s

Qwen 3.6 27B

27B

43.1 tok/s

Qwen3-VL 30B A3B Instruct

30B

102.5 tok/s

Qwen 3.5 35B A3B

35B

55.5 tok/s

Frequently asked questions

Can RTX 3090 24GB run Qwen 2.5 14B?

Yes, RTX 3090 24GB can run Qwen 2.5 14B with a S grade (Runs well). Expected decode speed: 82.9 tok/s.

How much VRAM does Qwen 2.5 14B need?

Qwen 2.5 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 14B?

The recommended quantization for Qwen 2.5 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 14B run at on RTX 3090 24GB?

On RTX 3090 24GB, Qwen 2.5 14B achieves approximately 82.9 tokens per second decode speed with a time-to-first-token of 2336ms using Q4_K_M quantization.

Can RTX 3090 24GB run Qwen 2.5 14B for coding?

For coding workloads, Qwen 2.5 14B on RTX 3090 24GB receives a S grade with 82.9 tok/s and 65K context.

What context window can Qwen 2.5 14B use on RTX 3090 24GB?

On RTX 3090 24GB, Qwen 2.5 14B can safely use up to 65K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.