NVIDIA GeForce RTX 4080
NVIDIA · 16GBGDDR6X · Can run 81 models
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| Manufacturer | NVIDIA |
| VRAM | 16 GB |
| Memory Type | GDDR6X |
| Architecture | Ada Lovelace |
| CUDA Cores | 9,728 |
| Tensor Cores | 304 |
| Bandwidth | 717 GB/s |
| TDP | 320W |
| MSRP | $1,199 |
| Released | Nov 16, 2022 |
AI Notes
The RTX 4080 is a capable GPU for running local AI models. With 16GB of GDDR6X VRAM, it handles 13B-parameter models well and can run some 30B models with Q4 quantization. Tensor cores accelerate inference, making it suitable for interactive AI applications.
Compatible Models
| Model | Parameters | Best Quant | VRAM Used | Fit | Est. Speed |
|---|---|---|---|---|---|
| Qwen 3 0.6B | 600M | Q4_K_M | 2.5 GB | Runs | ~287 tok/s |
| Qwen 3.5 0.8B | 800M | Q4_K_M | 1.5 GB | Runs | ~478 tok/s |
| Gemma 3 1B | 1B | Q8_0 | 2 GB | Runs | ~359 tok/s |
| Llama 3.2 1B | 1B | Q8_0 | 3 GB | Runs | ~239 tok/s |
| DeepSeek R1 1.5B | 1.5B | Q8_0 | 3 GB | Runs | ~239 tok/s |
| SmolLM2 1.7B | 1.7B | Q8_0 | 2.7 GB | Runs | ~266 tok/s |
| Gemma 2 2B | 2B | Q8_0 | 4 GB | Runs | ~179 tok/s |
| Gemma 3n E2B | 2B | Q4_K_M | 3.3 GB | Runs | ~217 tok/s |
| Gemma 4 E2B | 2B | Q4_K_M | 4 GB | Runs | ~179 tok/s |
| Qwen 3.5 2B | 2B | Q4_K_M | 3 GB | Runs | ~239 tok/s |
| Llama 3.2 3B | 3B | Q8_0 | 5 GB | Runs | ~143 tok/s |
| StarCoder2 3B | 3B | Q4_K_M | 3.5 GB | Runs | ~205 tok/s |
| Phi-3 Mini 3.8B | 3.8B | Q8_0 | 5.8 GB | Runs | ~124 tok/s |
| Phi-4 Mini 3.8B | 3.8B | Q4_K_M | 4.5 GB | Runs | ~159 tok/s |
| Gemma 3 4B | 4B | Q4_K_M | 5 GB | Runs | ~143 tok/s |
| Gemma 3n E4B | 4B | Q4_K_M | 4.5 GB | Runs | ~159 tok/s |
| Gemma 4 E4B | 4B | Q4_K_M | 6 GB | Runs | ~120 tok/s |
| Qwen 3 4B | 4B | Q4_K_M | 4.5 GB | Runs | ~159 tok/s |
| Qwen 3.5 4B | 4B | Q4_K_M | 4.5 GB | Runs | ~159 tok/s |
| Yi 1.5 6B | 6B | Q4_K_M | 5 GB | Runs | ~143 tok/s |
| Codestral Mamba 7B | 7B | Q4_K_M | 6.9 GB | Runs | ~104 tok/s |
| DeepSeek R1 7B | 7B | Q8_0 | 9 GB | Runs | ~80 tok/s |
| Falcon 3 7B | 7B | Q4_K_M | 6.8 GB | Runs | ~105 tok/s |
| InternLM 2.5 7B | 7B | Q4_K_M | 5.5 GB | Runs | ~130 tok/s |
| Mistral 7B | 7B | Q8_0 | 9 GB | Runs | ~80 tok/s |
| OpenChat 3.5 7B | 7B | Q4_K_M | 6.9 GB | Runs | ~104 tok/s |
| Qwen 2.5 7B | 7B | Q8_0 | 9 GB | Runs | ~80 tok/s |
| Qwen 2.5 Coder 7B | 7B | Q8_0 | 9 GB | Runs | ~80 tok/s |
| Qwen 2.5 VL 7B | 7B | Q4_K_M | 7 GB | Runs | ~102 tok/s |
| StarCoder2 7B | 7B | Q4_K_M | 5.5 GB | Runs | ~130 tok/s |
| WizardLM 2 7B | 7B | Q4_K_M | 6.9 GB | Runs | ~104 tok/s |
| Aya Expanse 8B | 8B | Q4_K_M | 6.5 GB | Runs | ~110 tok/s |
| Cogito 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~96 tok/s |
| DeepSeek R1 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~96 tok/s |
| Dolphin 3 8B | 8B | Q4_K_M | 6 GB | Runs | ~120 tok/s |
| Granite 3.3 8B | 8B | Q8_0 | 10 GB | Runs | ~72 tok/s |
| Llama 3.1 8B | 8B | Q8_0 | 10 GB | Runs | ~72 tok/s |
| Nemotron 3 Nano 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~96 tok/s |
| Nous Hermes 2 8B | 8B | Q4_K_M | 6 GB | Runs | ~120 tok/s |
| Qwen 3 8B | 8B | Q4_K_M | 7.5 GB | Runs | ~96 tok/s |
| Gemma 2 9B | 9B | Q8_0 | 11 GB | Runs | ~65 tok/s |
| Qwen 3.5 9B | 9B | Q4_K_M | 7.5 GB | Runs | ~96 tok/s |
| Yi 1.5 9B | 9B | Q4_K_M | 6.5 GB | Runs | ~110 tok/s |
| Yi Coder 9B | 9B | Q4_K_M | 8 GB | Runs | ~90 tok/s |
| Falcon 3 10B | 10B | Q4_K_M | 8.5 GB | Runs | ~84 tok/s |
| Llama 3.2 Vision 11B | 11B | Q4_K_M | 8.5 GB | Runs | ~84 tok/s |
| Gemma 3 12B | 12B | Q4_K_M | 10.5 GB | Runs | ~68 tok/s |
| Mistral Nemo 12B | 12B | Q4_K_M | 9.5 GB | Runs | ~75 tok/s |
| DeepSeek R1 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~72 tok/s |
| Phi-4 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~72 tok/s |
| Phi-4 Reasoning 14B | 14B | Q4_K_M | 11 GB | Runs | ~65 tok/s |
| Qwen 2.5 14B | 14B | Q4_K_M | 9.9 GB | Runs | ~72 tok/s |
| Qwen 2.5 Coder 14B | 14B | Q4_K_M | 12 GB | Runs | ~60 tok/s |
| Qwen 3 14B | 14B | Q4_K_M | 12 GB | Runs | ~60 tok/s |
| InternLM 2.5 20B | 20B | Q4_K_M | 12 GB | Runs | ~60 tok/s |
| Qwen 3.5 35B A3B | 35B | Q4_K_M | 12 GB | Runs | ~60 tok/s |
| gpt-oss 20B | 21B | MXFP4 | 15 GB | Runs (tight) | ~48 tok/s |
| Codestral 22B | 22B | Q4_K_M | 14.7 GB | Runs (tight) | ~49 tok/s |
| StarCoder2 15B | 15B | Q8_0 | 17 GB | CPU Offload | ~13 tok/s |
| Devstral 24B | 24B | Q4_K_M | 17 GB | CPU Offload | ~13 tok/s |
| Magistral Small 24B | 24B | Q4_K_M | 17 GB | CPU Offload | ~13 tok/s |
| Mistral Small 3.1 24B | 24B | Q4_K_M | 18 GB | CPU Offload | ~12 tok/s |
| Gemma 4 26B | 26B | Q4_K_M | 20 GB | CPU Offload | ~11 tok/s |
| Gemma 2 27B | 27B | Q4_K_M | 17.7 GB | CPU Offload | ~12 tok/s |
| Gemma 3 27B | 27B | Q4_K_M | 20 GB | CPU Offload | ~11 tok/s |
| Qwen 3.5 27B | 27B | Q4_K_M | 19 GB | CPU Offload | ~11 tok/s |
| Qwen 3.6 27B | 27B | Q4_K_M | 20 GB | CPU Offload | ~11 tok/s |
| Qwen 3 30B-A3B (MoE) | 30B | Q4_K_M | 22 GB | CPU Offload | ~10 tok/s |
| Gemma 4 31B | 31B | Q4_K_M | 22 GB | CPU Offload | ~10 tok/s |
| Aya Expanse 32B | 32B | Q4_K_M | 22 GB | CPU Offload | ~10 tok/s |
| Cogito 32B | 32B | Q4_K_M | 21.5 GB | CPU Offload | ~10 tok/s |
| DeepSeek R1 32B | 32B | Q4_K_M | 20.7 GB | CPU Offload | ~11 tok/s |
| Qwen 2.5 32B | 32B | Q4_K_M | 20.7 GB | CPU Offload | ~11 tok/s |
| Qwen 2.5 Coder 32B | 32B | Q4_K_M | 23 GB | CPU Offload | ~9 tok/s |
| Qwen 3 32B | 32B | Q4_K_M | 23 GB | CPU Offload | ~9 tok/s |
| QwQ 32B | 32B | Q4_K_M | 21.5 GB | CPU Offload | ~10 tok/s |
| Laguna XS 2.1 | 33B | Q4_K_M | 22 GB | CPU Offload | ~10 tok/s |
| WizardCoder 33B | 33B | Q4_K_M | 22 GB | CPU Offload | ~10 tok/s |
| Nous Hermes 2 34B | 34B | Q4_K_M | 19 GB | CPU Offload | ~11 tok/s |
| Yi 1.5 34B | 34B | Q4_K_M | 21 GB | CPU Offload | ~10 tok/s |
| Command R 35B | 35B | Q4_K_M | 22.5 GB | CPU Offload | ~10 tok/s |
33 model(s) are too large for this hardware.