作者： Jakub Rusinowski · 最后更新： 2026年7月12日
10 GB VRAM限制于8B模型，但带宽非常快。RTX 3080 Ti / 3080 12GB变体对AI明显更好。
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
| TDP | 320 W |
| Architecture | Ampere GA102 |
| Release Year | 2020 |
| MSRP at Launch | $699 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 50–97 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 10 GB usable |
or compare on Vast.ai from $0.35/hr (typical low · varies)
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
All models below run comfortably in 10 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 2.5 Family | Qwen 2.5 14B Instruct · 9 GB VRAM · Q4_K_M · ollama run qwen2.5:14b |
| Gemma 2 Family | Gemma 2 9B IT · 6 GB VRAM · Q4_K_M · ollama run gemma2 |
| Phi-4 Mini | Phi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · ollama run phi4-mini |
| Mistral Family | Mistral NeMo 12B · 8 GB VRAM · Q4_K_M · ollama run mistral-nemo |
| SmolLM2 | SmolLM2 1.7B Instruct · 2 GB VRAM · Q4_K_M · ollama run smollm2:1.7b |
Install Ollama then run the recommended model for this GPU:
ollama run llama3.1:8b
Yes — the NVIDIA GeForce RTX 3080 (10GB) has 10 GB VRAM and runs 10 GB VRAM限制于8B模型，但带宽非常快。RTX 3080 Ti / 3080 12GB变体对AI明显更好。
The NVIDIA GeForce RTX 3080 (10GB) is estimated to run Llama 3.1 8B at 50–97 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 10 GB usable. These are modelled estimates, not measurements — see /en/methodology.
With 10 GB you can run: Llama 3.1 Family, Qwen 2.5 Family, Gemma 2 Family, Phi-4 Mini, Mistral Family. Use Ollama for the easiest setup: ollama run llama3.1:8b.
← All GPU Reviews | Check Your Hardware | Full Benchmarks | Can I Run It?