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 64k context it runs 40 of the 113 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q4_K_M, at about 29 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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q4_K_M | fits | 21.5 GB | 92k161k with q8 cache | 29tok/sest. | 1085 tok/s | chat, coding, agents |
| Qwen 3.6 27B Alibaba Qwen | Q5_K_M | fits | 23.4 GB | 64k112k with q8 cache | 26tok/sest. | 1085 tok/s | chat, coding |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q4_K_M | fits | 23.1 GB | 74k116k with q8 cache | 115tok/sest. | 6531 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | fits | 20.8 GB | 101k178k with q8 cache | 30tok/sest. | 1085 tok/s | chat, coding, agents |
| Gemma 4 26B-A4B | UD-Q5_K_M | fits | 22.2 GB | 110k178k with q8 cache | 78tok/sest. | 6687 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | fits | 22.9 GB | 84k131k with q8 cache | 116tok/sest. | 6531 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | fits | 21.4 GB | 98k169k with q8 cache | 57tok/sest. | 3240 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.9 GB | 128k | 93tok/sest. | 4999 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.2 GB | 256k | 44tok/sest. | 2571 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.0 GB | 256k | 53tok/sest. | 3146 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q4_K_M | fits | 21.9 GB | 81k128k with q8 cache | 28tok/sest. | 1215 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q6_K | fits | 21.4 GB | 76k139k with q8 cache | 29tok/sest. | 1504 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q6_K | fits | 22.4 GB | 40k | 27tok/sest. | 1317 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.2 GB | 99k128k with q8 cache | 34tok/sest. | 2079 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.2 GB | 40k | 34tok/sest. | 2079 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q5_K_M | fits | 23.3 GB | 16k | 26tok/sest. | 1322 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.3 GB | 256k | 94tok/sest. | 5454 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.0 GB | 103k187k with q8 cache | 34tok/sest. | 2057 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 19.8 GB | 86k128k with q8 cache | 31tok/sest. | 1901 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 10.5 GB | 128k | 62tok/sest. | 4121 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.5 GB | 125k | 88tok/sest. | 8795 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.2 GB | 126k128k with q8 cache | 41tok/sest. | 2234 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.3 GB | 32k | 468tok/sest. | 19505 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.6 GB | 256k | 382tok/sest. | 22115 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.2 GB | 256k | 277tok/sest. | 12056 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 4.6 GB | 128k | 166tok/sest. | 8078 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.2 GB | 128k | 114tok/sest. | 4553 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.0 GB | 128k | 103tok/sest. | 8150 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.5 GB | 128k | 91tok/sest. | 5522 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.5 GB | 32k | 91tok/sest. | 5192 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 19.6 GB | 128k | 71tok/sest. | 5605 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.4 GB | 128k | 70tok/sest. | 3467 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 9.7 GB | 128k | 68tok/sest. | 3580 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q5_K_M | fits | 23.3 GB | 65k115k with q8 cache | 54tok/sest. | 5038 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.1 GB | 128k | 53tok/sest. | 2616 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 12.9 GB | 128k | 49tok/sest. | 1765 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.5 GB | 64k | 43tok/sest. | 1765 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.0 GB | 112k128k with q8 cache | 37tok/sest. | 2234 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.0 GB | 103k187k with q8 cache | 34tok/sest. | 2057 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q5_K_M | fits | 22.9 GB | 66k122k with q8 cache | 27tok/sest. | 1202 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.7 GB | – | 13tok/sest. | 1648 tok/s | chat |
| Gemma 4 31B | Q4_K_M | offload | 23.9 GB | 57k110k with q8 cache | 21tok/sest. | 977 tok/s | chat, coding |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.8 GB | – | 14tok/sest. | 3591 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.9 GB | – | 18tok/sest. | 1653 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | 57k105k with q8 cache | 17tok/sest. | 1040 tok/s | chat, coding, agents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.8 GB | – | 17tok/sest. | 4097 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.1 GB | – | 22tok/sest. | 6487 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.6 GB | – | 47tok/sest. | 4562 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.4 GB | 54k97k with q8 cache | 32tok/sest. | 2280 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.5 GB | 16k30k with q8 cache | 4tok/sest. | 437 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.4 GB | 57k105k with q8 cache | 17tok/sest. | 1040 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.6 GB | 16k30k with q8 cache | 4tok/sest. | 540 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | 57k105k with q8 cache | 17tok/sest. | 1054 tok/s | chat, coding, agents |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.4 GB | 40k | 17tok/sest. | 1054 tok/s | chat, coding |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.4 GB | 40k | 17tok/sest. | 1054 tok/s | chat, coding, agents |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.4 GB | 57k105k with q8 cache | 17tok/sest. | 1040 tok/s | chat, coding, agents |
| granite 4.2 30b IBM | Q4_K_M | offload | 33.9 GB | 23k42k with q8 cache | 4tok/sest. | 646 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 96.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.1 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 86.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.6 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 61.8 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 54.8 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.5 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 60.7 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.0 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 160.9 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 146.8 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 71.8 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 225.7 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.5 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.4 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 752.9 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.5 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.4 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 131.8 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 255.3 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 92.8 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 (Q4_K_M) fits fully in its memory at 64k context and generates at about 29 tok/s, an estimate from its memory bandwidth. 40 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 97 GB at 64k 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 64k context. See the best hardware for local AI at every budget.