作者: Jakub Rusinowski · 最后更新: 2026年7月12日
16 GB VRAM,价格与性能比出色。支持14B以内所有模型,且有充足的上下文窗口空间。
| VRAM | 16 GB |
| Memory Bandwidth | 736 GB/s |
| TDP | 320 W |
| Architecture | Ada Lovelace AD103 |
| Release Year | 2024 |
| MSRP at Launch | $999 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 68–130 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 16 GB usable |
or compare on Vast.ai from $0.35/hr (typical low · varies)
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All models below run comfortably in 16 GB VRAM with Q4_K_M quantization.
| Llama 3.1 Family | Llama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · ollama run llama3.1 |
| Qwen 3 | Qwen 3 14B · 10 GB VRAM · Q4_K_M · ollama run qwen3:14b |
| Gemma 3 | Gemma 3 12B Instruct · 8 GB VRAM · Q4_K_M · ollama run gemma3:12b |
| Phi-4 Family | Phi-4 (14B) · 9 GB VRAM · Q4_K_M · ollama run phi4 |
| Phi-4 Mini | Phi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · ollama run phi4-mini |
| Mistral Family | Mistral Small 3 (24B) · 15 GB VRAM · Q4_K_M · ollama run mistral-small |
| DeepSeek R1 | DeepSeek R1 Distill Qwen 14B · 9 GB VRAM · Q4_K_M · ollama run deepseek-r1:14b |
| Qwen 2.5 Family | Qwen 2.5 14B Instruct · 9 GB VRAM · Q4_K_M · ollama run qwen2.5:14b |
Install Ollama then run the recommended model for this GPU:
ollama run qwen3:14b
Yes — the NVIDIA GeForce RTX 4080 Super has 16 GB VRAM and runs 16 GB VRAM,价格与性能比出色。支持14B以内所有模型,且有充足的上下文窗口空间。
The NVIDIA GeForce RTX 4080 Super is estimated to run Llama 3.1 8B at 68–130 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 16 GB usable. These are modelled estimates, not measurements — see /en/methodology.
With 16 GB you can run: Llama 3.1 Family, Qwen 3, Gemma 3, Phi-4 Family, Phi-4 Mini. Use Ollama for the easiest setup: ollama run qwen3:14b.
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