NVIDIA GeForce RTX 4090
24 GB · 1,008 GB/s · 450 W
In short
The NVIDIA GeForce RTX 4090 has 24 GB of GDDR6X memory with 1,008 GB/s of bandwidth, which sets how fast it generates text. At 32k context it runs 48 of the 113 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q5_K_M, at about 27 tok/s (estimated). The best new price for the NVIDIA GeForce RTX 4090 in Germany is 3.955 € at eBay; used, it starts at 2.800 € (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Germany, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayMSI GeForce RTX 4090 Gaming X Trio 24G | used, asking price | 2.800 € | In stock | 1 h ago | Buy |
| eBayMSI GeForce RTX 4090 Ventus 3X 24 GB GDDR6X | used, asking price | 2.830 € | In stock | 1 h ago | Buy |
| eBayPalit RTX 4090 24GB GDDR6X VRAM GameRock OmniBlack | used, asking price | 2.850 € | In stock | 1 h ago | Buy |
| eBayGIGABYTE GeForce RTX 4090 AERO OC 24G Grafikkarte | used, asking price | 2.849 €+ 15 € delivery | In stock | 1 h ago | Buy |
| eBayPalit GeForce RTX 4090 GameRock OC 24GB GDDR6X Grafikkarte | used, asking price | 2.850 €+ 15 € delivery | In stock | 1 h ago | Buy |
| eBayMSI GeForce RTX 4090 GAMING X TRIO 24GB GDDR6X | used, asking price | 2.990 € | In stock | 1 h ago | Buy |
| eBayASUS ROG Strix GeForce RTX 4090 OC White 24GB Grafikkarte | used, asking price | 3.000 € | In stock | 1 h ago | Buy |
| eBayPalit GeForce RTX 4090 GameRock OC 24GB GDDR6X Grafikkarte | used, asking price | 3.000 € | In stock | 1 h ago | Buy |
| eBayGigabyte Geforce RTX 4090 Windforce v2 24G Grafikkarte | used, asking price | 3.000 € | In stock | 1 h ago | Buy |
| eBayMSI GeForce RTX 4090 SUPRIM x Liquid 24g NVIDIA 24GB GDDR6X Grafikkarte | used, asking price | 3.000 €+ 8 € delivery | In stock | 5 h ago | Buy |
| eBayMSI GeForce RTX 4090 SUPRIM LIQUID 24GB GDDR6X Grafikkarte | used, asking price | 3.150 € | In stock | 1 h ago | Buy |
| eBayPalit GeForce RTX 4090 GameRock OC 24GB GDDR6X Grafikkarte | used, asking price | 3.150 €+ 8 € delivery | In stock | 1 h ago | Buy |
| eBayNVIDIA GeForce RTX 4090 Founders Edition 24GB Grafikkarte inkl. Stromadapter | used, asking price | 3.200 €+ 28 € delivery | In stock | 1 h ago | Buy |
| eBayASUS TUF Gaming GeForce RTX 4090 24GB GDDR6X GPU Grafikkarte | used, asking price | 3.299 € | In stock | 1 h ago | Buy |
| eBay24GB ASUS TUF Gaming Nvidia RTX O24G OG OC Edition GDDR6X 4090 Grafikkarte | New | 3.955 €+ 15 € delivery | In stock | 1 h ago | Buy |
Used on eBay: median asking price 3.200 €, most between 2.955 € and 3.463 € (24 listings, 2026-10-15).
Price history
Lowest price shown each day over the last 90 days.
Not enough price history yet.
What it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q5_K_M | fits | 22.5 GB | 44k78k with q8 cache | 27tok/sest. | 1198 tok/s | chat, coding |
| Qwen 3.6 27B Alibaba Qwen | Q5_K_M | fits | 21.2 GB | 64k112k with q8 cache | 29tok/sest. | 1198 tok/s | chat, coding |
| Gemma 4 31B | Q4_K_M | fits | 21.2 GB | 57k110k with q8 cache | 29tok/sest. | 1067 tok/s | chat, coding |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q4_K_M | fits | 22.3 GB | 74k116k with q8 cache | 145tok/sest. | 8550 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q5_K_M | fits | 21.3 GB | 62k110k with q8 cache | 29tok/sest. | 1198 tok/s | chat, coding |
| Gemma 4 26B-A4B | UD-Q6_K | fits | 23.3 GB | 36k62k with q8 cache | 84tok/sest. | 7606 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | fits | 22.1 GB | 84k131k with q8 cache | 146tok/sest. | 8550 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q5_K_M | fits | 22.5 GB | 48k82k with q8 cache | 70tok/sest. | 4464 tok/s | chat, coding, agents |
| Devstral Small 2 24B Mistral AI | Q5_K_M | fits | 21.5 GB | 43k79k with q8 cache | 28tok/sest. | 1264 tok/s | chat, coding |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.9 GB | 128k | 116tok/sest. | 6383 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | fits | 21.2 GB | 54k97k with q8 cache | 74tok/sest. | 3932 tok/s | chat, coding, agents |
| Gemma 4 12B | Q8_0 | fits | 13.5 GB | 256k | 46tok/sest. | 2777 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.8 GB | 256k | 59tok/sest. | 3461 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q5_K_M | fits | 21.5 GB | 43k79k with q8 cache | 28tok/sest. | 1264 tok/s | chat, coding |
| Gemma 3 27B | Q5_K_M | fits | 21.7 GB | 51k95k with q8 cache | 28tok/sest. | 1271 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 19.3 GB | 57k104k with q8 cache | 32tok/sest. | 1922 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 20.5 GB | 40k | 30tok/sest. | 1728 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.5 GB | 99k128k with q8 cache | 46tok/sest. | 2851 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.5 GB | 40k | 46tok/sest. | 2851 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 21.6 GB | 16k | 28tok/sest. | 1737 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.1 GB | 256k | 112tok/sest. | 6475 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.5 GB | 103k187k with q8 cache | 46tok/sest. | 2754 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 14.6 GB | 86k128k with q8 cache | 43tok/sest. | 2622 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 9.4 GB | 128k | 68tok/sest. | 4348 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.8 GB | 125k | 140tok/sest. | 14221 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.0 GB | 126k128k with q8 cache | 57tok/sest. | 3012 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.8 GB | 32k | 669tok/sest. | 30972 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 507tok/sest. | 29093 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 337tok/sest. | 13870 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.5 GB | 128k | 221tok/sest. | 11651 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.7 GB | 128k | 153tok/sest. | 6958 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.4 GB | 128k | 128tok/sest. | 7881 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.4 GB | 32k | 128tok/sest. | 7227 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.4 GB | 128k | 118tok/sest. | 10268 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 6.8 GB | 128k | 99tok/sest. | 5049 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 7.0 GB | 128k | 95tok/sest. | 5292 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 18.4 GB | 128k | 88tok/sest. | 7715 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q6_K | fits | 23.1 GB | 35k63k with q8 cache | 84tok/sest. | 7925 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.2 GB | 128k | 63tok/sest. | 3405 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.5 GB | 128k | 55tok/sest. | 2371 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 12.8 GB | 112k128k with q8 cache | 49tok/sest. | 3012 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.1 GB | 64k | 48tok/sest. | 2371 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.5 GB | 103k187k with q8 cache | 46tok/sest. | 2754 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 21.5 GB | 41k76k with q8 cache | 28tok/sest. | 1627 tok/s | chat, coding |
| Devstral Small 2507 Mistral AI | Q5_K_M | fits | 21.5 GB | 43k79k with q8 cache | 28tok/sest. | 1283 tok/s | chat, coding |
| Magistral Small 2506 Mistral AI | Q5_K_M | fits | 21.5 GB | 40k | 28tok/sest. | 1283 tok/s | chat, coding |
| Magistral Small 2507 Mistral AI | Q5_K_M | fits | 21.5 GB | 40k | 28tok/sest. | 1283 tok/s | chat, coding |
| Magistral Small 2509 Mistral AI | Q5_K_M | fits | 21.5 GB | 43k79k with q8 cache | 28tok/sest. | 1264 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.7 GB | – | 16tok/sest. | 2075 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 46.9 GB | – | 18tok/sest. | 4694 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.0 GB | – | 22tok/sest. | 2354 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 48.8 GB | – | 4tok/sest. | 712 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 46.9 GB | – | 22tok/sest. | 5586 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 33.7 GB | – | 24tok/sest. | 7916 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.2 GB | – | 55tok/sest. | 6467 tok/s | chat, coding, long documents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.3 GB | 16k30k with q8 cache | 9tok/sest. | 678 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.4 GB | 16k30k with q8 cache | 9tok/sest. | 777 tok/s | chat |
| granite 4.2 30b IBM | Q4_K_M | offload | 25.7 GB | 23k42k with q8 cache | 12tok/sest. | 926 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 93.8 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.2 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 78.8 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.5 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.2 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 50.5 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 379.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.2 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.0 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 135.6 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 65.9 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 72.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.0 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 423.6 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.5 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.0 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 123.9 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 251.4 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 81.6 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- GeForce RTX 4090
- Memory
- 24 GB GDDR6X
- Memory bus
- 384-bit
- Memory bandwidth
- 1,008 GB/s
- FP16 compute
- 165 TFLOPS
- Software
- CUDA
- Board power
- 450 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA GeForce RTX 4090 have for AI models?
- The NVIDIA GeForce RTX 4090 has 24 GB of GDDR6X memory with 1,008 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA GeForce RTX 4090 can run locally?
- Qwen 3.8 27B (Q5_K_M) fits fully in its memory at 32k context and generates at about 27 tok/s, an estimate from its memory bandwidth. 48 of the 113 models we track fit at that context.
- Can the NVIDIA GeForce RTX 4090 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 94 GB at 32k context, more than the NVIDIA GeForce RTX 4090 and system RAM can hold.
- How much does the NVIDIA GeForce RTX 4090 cost in Germany?
- The best new price for the NVIDIA GeForce RTX 4090 in Germany is 3.955 € at eBay; used, it starts at 2.800 € (asking price).
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.