NVIDIA GeForce RTX 4080 Super
NVIDIA · 16GB GDDR6X · Can run 36 models
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| Manufacturer | NVIDIA |
| VRAM | 16 GB |
| Memory Type | GDDR6X |
| Architecture | Ada Lovelace |
| CUDA Cores | 10,240 |
| Bandwidth | 736 GB/s |
| TDP | 320W |
| MSRP | $999 |
| Released | Jan 31, 2024 |
AI Notes
The RTX 4080 Super is a high-end option with 16GB VRAM and 736 GB/s bandwidth. It comfortably runs 13B models and can handle some 30B models with aggressive quantization. The high bandwidth ensures fast token generation, making it excellent for interactive AI use.
Compatible Models
| Model | Parameters | Best Quant | VRAM Used | Fit | Est. Speed |
|---|---|---|---|---|---|
| Gemma 3 1B | 1B | Q8_0 | 2 GB | Runs | ~368 tok/s |
| Llama 3.2 1B | 1B | Q8_0 | 3 GB | Runs | ~245 tok/s |
| DeepSeek R1 1.5B | 1.5B | Q8_0 | 3 GB | Runs | ~245 tok/s |
| Gemma 2 2B | 2B | Q8_0 | 4 GB | Runs | ~184 tok/s |
| Llama 3.2 3B | 3B | Q8_0 | 5 GB | Runs | ~147 tok/s |
| Phi-3 Mini 3.8B | 3.8B | Q8_0 | 5.8 GB | Runs | ~127 tok/s |
| Phi-4 Mini 3.8B | 3.8B | Q4_K_M | 4.5 GB | Runs | ~164 tok/s |
| Gemma 3 4B | 4B | Q4_K_M | 5 GB | Runs | ~147 tok/s |
| Qwen 3 4B | 4B | Q4_K_M | 4.5 GB | Runs | ~164 tok/s |
| DeepSeek R1 7B | 7B | Q8_0 | 9 GB | Runs | ~82 tok/s |
| Mistral 7B | 7B | Q8_0 | 9 GB | Runs | ~82 tok/s |
| Qwen 2.5 7B | 7B | Q8_0 | 9 GB | Runs | ~82 tok/s |
| Qwen 2.5 Coder 7B | 7B | Q8_0 | 9 GB | Runs | ~82 tok/s |
| DeepSeek R1 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~98 tok/s |
| Llama 3.1 8B | 8B | Q8_0 | 10 GB | Runs | ~74 tok/s |
| Qwen 3 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~98 tok/s |
| Gemma 2 9B | 9B | Q8_0 | 11 GB | Runs | ~67 tok/s |
| Gemma 3 12B | 12B | Q4_K_M | 10.5 GB | Runs | ~70 tok/s |
| Mistral Nemo 12B | 12B | Q4_K_M | 9.5 GB | Runs | ~77 tok/s |
| DeepSeek R1 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~74 tok/s |
| Phi-4 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~74 tok/s |
| Qwen 2.5 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~74 tok/s |
| Qwen 2.5 Coder 14B | 14B | Q4_K_M | 12 GB | Runs | ~61 tok/s |
| Qwen 3 14B | 14B | Q4_K_M | 12 GB | Runs | ~61 tok/s |
| Codestral 22B | 22B | Q4_K_M | 14.7 GB | Runs (tight) | ~50 tok/s |
| StarCoder2 15B | 15B | Q8_0 | 17 GB | CPU Offload | ~43 tok/s |
| Devstral 24B | 24B | Q4_K_M | 17 GB | CPU Offload | ~43 tok/s |
| Mistral Small 3.1 24B | 24B | Q4_K_M | 18 GB | CPU Offload | ~41 tok/s |
| Gemma 2 27B | 27B | Q4_K_M | 17.7 GB | CPU Offload | ~42 tok/s |
| Gemma 3 27B | 27B | Q4_K_M | 20 GB | CPU Offload | ~37 tok/s |
| Qwen 3 30B-A3B (MoE) | 30B | Q4_K_M | 22 GB | CPU Offload | ~33 tok/s |
| DeepSeek R1 32B | 32B | Q4_K_M | 20.7 GB | CPU Offload | ~36 tok/s |
| Qwen 2.5 32B | 32B | Q4_K_M | 20.7 GB | CPU Offload | ~36 tok/s |
| Qwen 2.5 Coder 32B | 32B | Q4_K_M | 23 GB | CPU Offload | ~32 tok/s |
| Qwen 3 32B | 32B | Q4_K_M | 23 GB | CPU Offload | ~32 tok/s |
| Command R 35B | 35B | Q4_K_M | 22.5 GB | CPU Offload | ~33 tok/s |
7
model(s) are too large for this hardware.