Qwen 3 14B — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 28 kwietnia 2025

Model library → Qwen 3 → Qwen 3 14B

A powerhouse 14B model with hybrid thinking. Beats Qwen 2.5 72B in reasoning benchmarks despite being 5x smaller. Perfect for RTX 4070/4080 users who want frontier-level reasoning locally.

Qwen 3 14B needs about 10 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters14 Billion
Context window128,000
ArchitectureDense
ProviderAlibaba Cloud
LicenceApache 2.0
Specified atQ4_K_M
System RAM24 GB
Record updated2025-04-28

Licence

Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K4.9 GB7.0 GB~104 tok/s (est.)Fits comfortably
Q3_K_M6.3 GB8.5 GB~87 tok/s (est.)Fits comfortably
Q4_K_M8.9 GB11.1 GB~67 tok/s (est.)Fits comfortably
Q5_K_M10.5 GB12.6 GB~59 tok/s (est.)Fits comfortably
Q6_K12.1 GB14.3 GB~52 tok/s (est.)Fits comfortably
Q8_015.7 GB17.9 GB~42 tok/s (est.)Fits comfortably
F1629.6 GB31.7 GB~4 tok/s (est.)Offloads to system RAM (slow)

Want the memory numbers alone, at every quantization level and your own context length? Use the Qwen 3 14B VRAM calculator.

Buy This HardwareIntel Arc B570 10GB — 10 GB VRAM · 150 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Qwen 3 14B is the Intel Arc B570 (10 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Qwen 3 14B

Install Ollama, then run:

ollama run qwen3:14b

Weights on Hugging Face: Qwen/Qwen3-14B.

Best for: reasoning, coding, math, rag.

Can I Run Qwen 3 14B on My GPU?

Other Qwen 3 Sizes

Qwen 3 14B — Frequently Asked Questions

How much VRAM does Qwen 3 14B need?
About 10 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Qwen 3 14B run on an RTX 4090 (24 GB)?
Yes. Qwen 3 14B needs about 10 GB at Q4_K_M, inside a 24 GB card, at an estimated 67 tokens/sec.
How do I run Qwen 3 14B locally?
Install Ollama and run `ollama run qwen3:14b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Qwen 3 come in?
Qwen 3 8B (6 GB), Qwen 3 14B (10 GB), Qwen 3 32B (21 GB), Qwen 3 30B-A3B (MoE) (19 GB), Qwen 3 235B-A22B (MoE) (143 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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