Qwen 3 14B needs ~11.5 GB VRAM. RTX 3080 10GB has 10.0 GB. With Q3_K_S quantization, expect ~47 tok/s.
Operating mode
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.
Select quantization to explore
3.2 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
30.6 tok/s
TTFT
6321 ms
Safe context
4K
Memory
13.2 GB / 10.0 GB
Offload
20%
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 0.9 GB of extra host RAM just for the offloaded portion, before OS and other tools.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Very compromised (needs ~1.4 GB host RAM) | 37.6 tok/s | 2810 ms | 4K |
| Coding | F | Too heavy | 30.6 tok/s | 6321 ms | 4K |
| Agentic Coding | F | Too heavy | 21.4 tok/s | 13147 ms | 4K |
| Reasoning | F | Too heavy | 30.6 tok/s | 7470 ms | 4K |
| RAG | F | Too heavy | 21.4 tok/s | 16434 ms | 4K |
How Qwen 3 14B (14B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | S93 |
Q3_K_SBest for your GPU | 3 | 6.9 GB | Low | S93 |
NVFP4 | 4 | 7.8 GB | Medium | F0 |
Q4_K_M | 4 | 8.5 GB | Medium | F0 |
Q5_K_M | 5 | 10.1 GB | High | F0 |
Q6_K | 6 | 11.5 GB | High | F0 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Qwen 3 14B on your machine.
Run
ollama run qwen3Opciones de mejora
RTX 3060 12GBMejor relación calidad-precioHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
~$329 MSRP
RTX 5060 Ti 16GBOpción económicaHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$449 MSRP
RTX 4060 Ti 16GBMejora NVIDIAHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$499 MSRP
Yes, RTX 3080 10GB can run Qwen 3 14B at Q3_K_S quantization (Very compromised (needs ~0.9 GB host RAM)). The recommended Q4_K_M requires 13.2 GB which exceeds available memory, but at Q3_K_S it needs only 11.5 GB. Expected decode speed: 47.2 tok/s.
Qwen 3 14B (14B parameters) requires approximately 13.2 GB at Q4_K_M quantization. On RTX 3080 10GB, it fits at Q3_K_S using 11.5 GB.
The recommended quantization is Q4_K_M, but on RTX 3080 10GB the best fitting quantization is Q3_K_S, which uses 11.5 GB.
On RTX 3080 10GB, Qwen 3 14B achieves approximately 47.2 tokens per second decode speed with a time-to-first-token of 4097ms using Q3_K_S quantization.
For coding workloads, Qwen 3 14B on RTX 3080 10GB receives a F grade with 30.6 tok/s and 4K context.
On RTX 3080 10GB, Qwen 3 14B can safely use up to 6K tokens of context at Q3_K_S quantization. The model's official context limit is 131K, but available memory constrains the safe maximum.
Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-14b-on-rtx-3080-10gb" 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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