The datacenter workhorse of the 2021–2023 AI wave, now the value pick for on-prem business inference: 80 GB HBM2e at 1.9 TB/s runs Llama 3.3 70B at Q4 entirely on one card. No official MSRP — single-unit street pricing has fallen well below launch levels as H100/B200 fleets displace it, and the used/refurb market is active. PCIe version shown; SXM needs an HGX carrier board.
| VRAM | 80 GB |
| Memory Bandwidth | 1935 GB/s |
| TDP | 300 W |
| Architecture | Ampere GA100 |
| Release Year | 2021 |
| MSRP at Launch | $15,000 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | ~145 tokens/sec |
| Inference Speed (Llama 3.3 70B Q4_K_M) | ~30 tokens/sec |
All models below run comfortably in 80 GB VRAM with Q4_K_M quantization.
| Llama 4 | 67 GB VRAM · Q4_K_M · ollama run llama4:scout |
| Llama 3.3 | 43 GB VRAM · Q2_K_XS (Tight) · ollama run llama3.3 |
| Llama 3.1 Family | 6 GB VRAM · Q4_K_M · ollama run llama3.1 |
| DeepSeek R1 | 20 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b |
| Qwen 3 | 80 GB VRAM · Q4_K_M · ollama run qwen3:235b-a22b |
| Qwen 3.5 | 74 GB VRAM · Q4_K_M · ollama run qwen3.5:122b |
| Qwen 3.6 | 22 GB VRAM · Q4_K_M · ollama run qwen3.6:35b-a3b |
| Gemma 3 | 17 GB VRAM · Q4_K_M · ollama run gemma3:27b |
Install Ollama then run the recommended model for this GPU:
ollama run llama3.3:70b
Yes — the NVIDIA A100 80GB has 80 GB VRAM and runs The datacenter workhorse of the 2021–2023 AI wave, now the value pick for on-prem business inference: 80 GB HBM2e at 1.9
The NVIDIA A100 80GB runs Llama 3.1 8B at ~145 tokens/sec with Q4_K_M quantization. For the 70B model it achieves ~30 tokens/sec.
With 80 GB you can run: Llama 4, Llama 3.3, Llama 3.1 Family, DeepSeek R1, Qwen 3. Use Ollama for the easiest setup: ollama run llama3.3:70b.
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