LLMLocal inference
Qwen3 14B
Weight estimates and planning VRAM for running Qwen3 14B locally at each quantization level. Compare the lowest reference-cost devices that clear the plan.
Q4 plan
10 GB
Q8 plan
18 GB
FP16 plan
33 GB
Context window
128 k tokens
Planning targets add 15% to weight estimates for runtime buffers and a modest KV cache. Long context or a different backend can require more. Official Qwen model card ↗
01 // GPUs that can run Qwen3 14B
Compatible hardware by quantization
Sorted by dated reference-cost estimates from Apr 30, 2026. These are not live offers.
Q4Q4_K_M (4-bit)
8GB weights · plan ≥10GBGPUVRAMPriceTier
Q8Q8_0 (8-bit)
15GB weights · plan ≥18GBGPUVRAMPriceTier
FP16FP16 (full precision)
28GB weights · plan ≥33GBGPUVRAMPriceTier
02 // Frequently asked
Qwen3 14B GPU questions
How much VRAM does Qwen3 14B need?
Qwen3 14B uses approximately 8GB for Q4 weights, 15GB at Q8, or 28GB at FP16. GPU Hunter adds 15% planning headroom for runtime buffers and a modest KV cache, producing targets of 10GB, 18GB, and 33GB respectively. Exact memory use varies by backend and context length.
What is the cheapest GPU to run Qwen3 14B?
Using GPU Hunter's 10GB Q4 planning target, the lowest reference-cost single device is the GeForce RTX 3060 12GB (12GB VRAM, dated estimate $249).
Can I run Qwen3 14B at FP16?
Potentially. Qwen3 14B uses about 28GB for FP16 weights and 33GB under GPU Hunter's planning allowance. Confirm the backend and context requirement before purchasing.
What quantization is best for Qwen3 14B?
Q4_K_M uses about 8GB for weights and is the most hardware-accessible option. Q8_0 uses about 15GB and trades more memory for fidelity. FP16 uses about 28GB before runtime and context overhead. The right choice depends on the task, backend, and context window.