Best Qwen Model for 16GB VRAM (16GB VRAM)
Getting the most Qwen out of a 16GB GPU
The best Qwen model for 16GB VRAM in 2026 is Qwen 3 14B — ~9GB at Q4_K_M, ~35 tokens/sec on an RTX 4080, with room for a long context. For coding, Qwen 2.5 Coder 14B is the pick. You can squeeze Qwen 2.5 32B at Q3 into 16GB with a short context, but a 14B at Q4 is faster and usually higher quality. Full-quality 32B wants 24GB.
Models that fit in 16GB VRAM
Tested reference: RTX 4080 / RTX 4060 Ti 16GB. Figures are for Q4_K_M with a modest context window.
| Model | Size | Build | VRAM used | Speed |
|---|---|---|---|---|
| WINNERQwen 3 14B Best Qwen that fits 16GB comfortably — hybrid thinking, 128K context. ollama pull qwen3:14b | 14B | Q4_K_M | ~9.0GB | ~35 tok/s |
| Qwen 2.5 Coder 14B Best Qwen coder at this tier — near-SOTA local code quality. ollama pull qwen2.5-coder:14b | 14B | Q4_K_M | ~9.0GB | ~34 tok/s |
| Qwen 3 14B (Q5) 16GB lets you run the 14B at Q5 for a small fidelity bump. ollama pull qwen3:14b-q5_K_M | 14B | Q5_K_M | ~11GB | ~30 tok/s |
| Qwen 2.5 32B (Q3) A 32B just fits at Q3 with short context — more knowledge, but slower/lower fidelity than the 14B. ollama pull qwen2.5:32b-instruct-q3_K_S | 32B | Q3_K_S | ~15GB | ~13 tok/s |
What won't fit in 16GB
- ✗Qwen 2.5 32B (Q4) (needs ~20GB) — Full-quality 32B needs 24GB.
- ✗Qwen 2.5 72B (needs ~42GB) — Needs 48GB.
How to fit more in 16GB
- →Prefer Qwen 3 14B at Q4/Q5 over Qwen 2.5 32B at Q3 — higher fidelity and roughly 2.5× the speed.
- →Use flash-attention to run the full 128K context that 16GB can hold for a 14B.
- →Qwen 3’s thinking mode adds latency but noticeably improves hard-reasoning answers — toggle per task.
Quick start
curl -fsSL https://ollama.com/install.sh | shollama run qwen3:14bGo from “it runs” to actually building
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Start learning free →Frequently asked questions
Which Qwen model is best for 16GB VRAM?
Qwen 3 14B for general use (~9GB, ~35 tok/s) and Qwen 2.5 Coder 14B for coding. Both fit 16GB comfortably at Q4 with a long context.
Can 16GB run Qwen 32B?
Only at Q3 with a short context (~13 tok/s). It works but a 14B at Q4 is faster and usually better on real tasks. For comfortable 32B use a 24GB card.
Qwen 3 14B vs Qwen 2.5 32B on 16GB?
The 14B at Q4 wins for most users — faster, full context, higher fidelity per token. Choose the 32B (Q3) only when you specifically need its broader knowledge and can accept the slowdown.
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