# Can I run Qwen3-14B on an RTX 3080? | What Can I Run AI? > No. Qwen3-14B needs about 11.3 GB at Q4_K_M, and RTX 3080 has 10.0 GB usable. What to run instead. Source: https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3080-10gb/ [Home](https://whatcanirunai.vercel.app/) / [Can I run it?](https://whatcanirunai.vercel.app/can-i-run/) / [Qwen3-14B](https://whatcanirunai.vercel.app/models/qwen3-14b/) / Qwen3-14B on an RTX 3080 **No.** Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3080 10GB has 10.0 GB usable at a \~4k context. # Can I run Qwen3-14B on an RTX 3080? Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3080 10GB has 10.0 GB usable. That figure is 10 GB of VRAM on the spec sheet, of which 10.0 GB is usable for weights and cache, at 760 GB/s memory bandwidth. Alibaba’s 14B Qwen3\. It sits in the sweet spot for 12–16 GB cards that want more quality than an 8B. These are estimates from [our formula](https://whatcanirunai.vercel.app/method/), not measured benchmarks. Quant that fits None of Q4, Q8 or FP16 needs 11.3 GB Memory needed 11.3 GB at Q4\_K\_M, \~4k context Usable VRAM 10.0 GB of 10 GB VRAM Est. tokens/sec n/a does not fit [Qwen3-14B](https://whatcanirunai.vercel.app/models/qwen3-14b/) · [GeForce RTX 3080 10GB](https://whatcanirunai.vercel.app/hardware/rtx-3080-10gb/) · [Everything this machine runs](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3080-10gb/) · [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/) ## Memory at each quant | Quant | Need vs 10.0 GB | Verdict | | -------- | --------------- | ------------- | | Q4\_K\_M | 11.3 GB | Q4Won’t fit | | Q8\_0 | 19.0 GB | Q8Won’t fit | | FP16 | 35.0 GB | FP16Won’t fit | ## Estimated tokens per second No speed estimate: Qwen3-14B does not fit in the 10.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload. ## Context headroom Even at a short \~4k context, the weights do not fit. Extending context would only increase the gap. __Context headroom for Qwen3-14B on an RTX 3080 at Q4\_K\_M__ | Context | KV cache (FP16) | Total at Q4\_K\_M | Verdict | | ------- | --------------- | ----------------- | --------- | | 4k | 0.7 GB | 11.3 GB | Won’t fit | | 8k | 1.3 GB | 12.0 GB | Won’t fit | | 16k | 2.7 GB | 13.3 GB | Won’t fit | | 32k | 5.4 GB | 16.0 GB | Won’t fit | | 64k | 10.7 GB | 21.4 GB | Won’t fit | | 128k | 21.5 GB | 32.1 GB | Won’t fit | From the model’s config. Try other sizes in the [VRAM calculator](https://whatcanirunai.vercel.app/vram-calculator/) or see the [context length guide](https://whatcanirunai.vercel.app/context-length/). ## What to do instead * Run [Gemma 3 12B](https://whatcanirunai.vercel.app/can-i-run/gemma-3-12b-it/rtx-3080-10gb/) instead (9.5 GB at Q4). It is a different model, not a drop-in, but it does fit this machine. * To hold Qwen3-14B at Q4, you need about 11.3 GB. The [GeForce RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3060-12gb/) has 12.0 GB usable ($329 list price). * Our estimate is only 1.3 GB over this machine’s usable memory, so a tighter quant or a shorter context may work in practice. We still mark it as a no under [the published formula](https://whatcanirunai.vercel.app/method/). * CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure. * See the [best GPU for this model family](https://whatcanirunai.vercel.app/best-gpu-for/qwen3/) and the [Qwen3-14B model page](https://whatcanirunai.vercel.app/models/qwen3-14b/). ## Other hardware for Qwen3-14B * [Qwen3-14B on an RTX 3060 12GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3060-12gb/)Tight * [Qwen3-14B on an RTX 3070 Ti](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-3070-ti/)Won’t fit * [Qwen3-14B on an RTX 4060 Ti 16GB](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4060-ti-16gb/)Fits * [Qwen3-14B on an RTX 4070 Ti Super](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4070-ti-super/)Fits * [Qwen3-14B on an RTX 4090](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-4090/)Fits * [Qwen3-14B on an RTX 5070 Ti](https://whatcanirunai.vercel.app/can-i-run/qwen3-14b/rtx-5070-ti/)Fits ## Other models on an RTX 3080 * [Qwen3-32B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/qwen3-32b/rtx-3080-10gb/)Won’t fit * [Qwen3-30B-A3B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/qwen3-30b-a3b/rtx-3080-10gb/)Won’t fit * [Qwen3.8-27B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/qwen3.8-27b/rtx-3080-10gb/)Won’t fit * [Gemma 3 27B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/gemma-3-27b-it/rtx-3080-10gb/)Won’t fit * [Gemma 4 31B on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/gemma-4-31b-it/rtx-3080-10gb/)Won’t fit * [gpt-oss-20b on an RTX 3080](https://whatcanirunai.vercel.app/can-i-run/gpt-oss-20b/rtx-3080-10gb/)Won’t fit ## Quick answers Can I run Qwen3-14B on an RTX 3080? No. Qwen3-14B at Q4\_K\_M needs about 11.3 GB, and the GeForce RTX 3080 10GB has 10.0 GB usable. How much VRAM does Qwen3-14B need? About 11.3 GB at Q4\_K\_M, 19.0 GB at Q8\_0 and 35.0 GB at FP16, estimated for a \~4k context. How fast is Qwen3-14B on an RTX 3080? We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow. What context length can I use? The weights already do not fit, so longer context is not the limiting factor. --- Agent guide: https://whatcanirunai.vercel.app/llms.txt · JSON API: https://whatcanirunai.vercel.app/developers/