Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026
Punkt odniesienia dla konsumenckich GPU do AI. 24 GB VRAM mieści w całości DeepSeek R1 32B i Llama 4 Scout. 165 t/s na Llama 3.1 8B.
| VRAM | 24 GB |
| Memory Bandwidth | 1008 GB/s |
| TDP | 450 W |
| Architecture | Ada Lovelace AD102 |
| Release Year | 2022 |
| MSRP at Launch | $1,599 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 86–165 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 24 GB usable |
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All models below run comfortably in 24 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 |
| DeepSeek R1 | DeepSeek R1 Distill Qwen 32B · 20 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b |
| Qwen 3 | Qwen 3 32B · 21 GB VRAM · Q4_K_M · ollama run qwen3:32b |
| Qwen 3.6 | Qwen 3.6 35B-A3B · 22 GB VRAM · Q4_K_M · ollama run qwen3.6:35b-a3b |
| Qwen 3.7 | Qwen 3.7 35B-A3B · 22 GB VRAM · Q4_K_M · qwen3-7 |
| Gemma 3 | Gemma 3 27B Instruct · 17 GB VRAM · Q4_K_M · ollama run gemma3:27b |
| Gemma 4 | Gemma 4 31B · 20 GB VRAM · Q4_K_M · ollama run gemma4:31b |
| Mistral Small 3.1 | Mistral Small 3.1 24B · 15 GB VRAM · Q4_K_M · ollama run mistral-small3.1 |
Install Ollama then run the recommended model for this GPU:
ollama run deepseek-r1:32b
Yes — the NVIDIA GeForce RTX 4090 has 24 GB VRAM and runs Punkt odniesienia dla konsumenckich GPU do AI. 24 GB VRAM mieści w całości DeepSeek R1 32B i Llama 4 Scout. 165 t/s na L
The NVIDIA GeForce RTX 4090 is estimated to run Llama 3.1 8B at 86–165 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 24 GB usable. These are modelled estimates, not measurements — see /en/methodology.
With 24 GB you can run: Llama 3.1 Family, DeepSeek R1, Qwen 3, Qwen 3.6, Qwen 3.7. Use Ollama for the easiest setup: ollama run deepseek-r1:32b.
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