Alibaba
Qwen 3 14B (14B parameters) requires approximately 12.8 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 15 GB of VRAM.
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— copy & paste to run locallyCopy-paste commands to run Qwen 3 14B on your machine.
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ollama run qwen3Quick specs
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Inference speed
Estimated decode speed (tokens/sec) for Qwen 3 14B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~152 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 151.8 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 96.9 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 88.4 | Tight |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 87.4 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 82.9 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 70.4 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 58.7 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 55.6 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 38.3 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 38.3 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 34.2 | Heavy offload |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 30.4 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 27.8 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 23.4 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 18.4 | Heavy offload |
| RTX 4060 8GB | 8 GB | Q4_K_M | 6.8 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
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Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | — |
Q3_K_S | 3 | 6.9 GB | Low | — |
NVFP4 | 4 | 7.8 GB | Medium | — |
Q4_K_M | 4 | 8.5 GB | Medium | — |
Q5_K_M | 5 | 10.1 GB | High | — |
Q6_K | 6 | 11.5 GB | High | — |
Q8_0 | 8 | 15.0 GB | Very High | — |
F16 | 16 | 28.7 GB | Maximum | — |
Quality benchmarks
Reasoning
General
Source: official · 2025-05-15
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
Qwen 3 14B (14B parameters) requires approximately 12.8 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, RX 7600 XT 16GB can run Qwen 3 14B with a compatibility score of 90/100. It provides 16 GB of memory and achieves approximately 21.1 tokens per second.
The recommended quantization for Qwen 3 14B is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
The top recommended hardware for Qwen 3 14B: RTX A4500 20GB (score: 96/100), RX 7900 XT 20GB (score: 96/100), RTX 4090 24GB (score: 96/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, Qwen 3 14B is well-suited for chat as well as reasoning. It was designed with these use cases in mind.
See also