Can Qwen 3 8B run on RTX 4090 24GB?

YES — Runs Great

S91Excellent

Measured on real hardware· rtx-4090-24gb

Qwen 3 8B needs ~10.4 GB VRAM. RTX 4090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~120 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: 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) — 10.4 GB, 120.0 tok/s, Runs well

10.4 GB required24.0 GB available

43% VRAM used

Fit status

Runs well

Decode

120.0 tok/s

TTFT

1613 ms

Safe context

115K

Memory

10.4 GB / 24.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.2 GB

Runtime0.9 GB

Headroom2.4 GB

See how fast it feels

See how fast it feelsQwen 3 8B on RTX 4090 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: 120.0 tok/s decode · 1.6s TTFT (warm) · 300 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	120.0 tok/s	880 ms	115K
Coding	S	Runs well	120.0 tok/s	1729 ms	115K
Agentic Coding	S	Runs well	120.0 tok/s	2347 ms	115K
Reasoning	S	Runs well	120.0 tok/s	1907 ms	115K
RAG	S	Runs well	120.0 tok/s	2933 ms	115K

Quantization options

How Qwen 3 8B (8B params) fits at each quantization level on RTX 4090 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	A84
Q3_K_S	3	3.9 GB	Low	A85
NVFP4	4	4.5 GB	Medium	S85
Q4_K_M	4	4.9 GB	Medium	S85
Q5_K_M	5	5.8 GB	High	S86
Q6_K	6	6.6 GB	High	S86
Q8_0	8	8.6 GB	Very High	S88
F16Best for your GPU	16	16.4 GB	Maximum	S90

Get started

Copy-paste commands to run Qwen 3 8B on your machine.

Run

ollama run qwen3:8b

Your hardware

More models your RTX 4090 24GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	83.4 tok/s
Qwen 3.5 27B	27B	S	34.8 tok/s
Qwen 3.6 27B	27B	S	20.2 tok/s
Qwen 3.6 35B A3B	35B	A	53.4 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	119.8 tok/s

Frequently asked questions

Can RTX 4090 24GB run Qwen 3 8B?

Yes, RTX 4090 24GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 120.0 tok/s.

How much VRAM does Qwen 3 8B need?

Qwen 3 8B (8B parameters) requires approximately 10.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 8B?

The recommended quantization for Qwen 3 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 8B run at on RTX 4090 24GB?

On RTX 4090 24GB, Qwen 3 8B achieves approximately 120.0 tokens per second decode speed with a time-to-first-token of 1729ms using Q4_K_M quantization.

Can RTX 4090 24GB run Qwen 3 8B for coding?

For coding workloads, Qwen 3 8B on RTX 4090 24GB receives a S grade with 120.0 tok/s and 115K context.

What context window can Qwen 3 8B use on RTX 4090 24GB?

On RTX 4090 24GB, Qwen 3 8B can safely use up to 115K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX 4090 24GB See all hardware for Qwen 3 8B

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<iframe src="https://willitrunai.com/embed/qwen-3-8b-on-rtx-4090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

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