Qwen3 14B · 10 GPUs measured first-party · llama.cpp Q4_K_M · Updated July 2026

What GPU Do You Need for Qwen3 14B?

Qwen3 14B is the middle child of the lineup: noticeably smarter than the 8B, but in our view not yet the tier where local work gets genuinely good, that starts at 30B-A3B and above. We measured it on 10 GPUs (llama.cpp, Q4_K_M): 165 tok/s on the B300, ~10GB peak VRAM, which makes 12GB the realistic minimum card class.

Benchmarked weights: Qwen/Qwen3-14B-GGUF

Honest positioning. With 14B you can start doing real local LLM work. It holds context better and hallucinates less than the 8B. But my honest advice is that if your hardware allows it, step up: the 30B-A3B MoE needs 20GB but generates nearly twice as fast in our measurements (309 vs 165 tok/s at the top of each chart) while being a stronger model. 14B is the right stop when your card has 12GB and nothing more: a $179 Arc B580 or an RTX 3060 12GB fits it, and nothing in the 30B class ever will.

Fit and throughput notes. The ~10GB measured peak makes 12GB cards a real but snug fit. Long contexts will push against the ceiling, so keep expectations modest there. On speed, the usual pattern holds: B300 wins the headline at 165 tok/s and 315W, the H200 does 155 tok/s at 123W, 2.4× the efficiency for a 6% speed loss. At the bottom, the L4 manages 28 tok/s, which is workable for a single user but nothing more.

Our verdict

Qwen3 14B: 165 tok/s peak, ~10GB floor: the best model that fits a 12GB card, and that's exactly how we'd use it. If you have 24GB, skip it for the 30B-A3B, which is both faster and stronger. Every number is first-party llama.cpp measurement with logged power.

FAQ

Can a 12GB card run Qwen3 14B?

Yes, ~10GB measured peak at Q4_K_M fits a 12GB card like the $179 Arc B580 or RTX 3060 12GB, though long contexts run close to the ceiling. 8GB cards don't fit it.

Should I run 14B or step up to 30B-A3B?

If you have 24GB of VRAM, step up: Qwen3 30B-A3B measured nearly twice as fast (309 vs 165 tok/s at the top of each chart) because only ~3B parameters are active per token, and it's a stronger model. 14B is the right choice specifically for 12GB cards.

How fast is Qwen3 14B on a datacenter card?

B300: 165 tok/s. H200: 155 tok/s at 2.4× better tokens-per-watt (1.26 vs 0.52). For a single-user session, anything above ~30 tok/s feels instant, even the A10G's 51 tok/s is comfortable.

Is 14B good enough for coding?

It's serviceable, but the coder-tuned models are the better tool: Qwen2.5-Coder 14B at the same size, or Qwen3 Coder 30B-A3B if you have the VRAM. We benchmark all of them on the same harness.

What quantization did you test?

Q4_K_M via llama.cpp: the quality-per-GB sweet spot most local users run, and the same pinned setup as every LLM on this site, so cross-model comparisons are apples to apples.