NVIDIA RTX 6000 Ada Generation
48 GB · 960 GB/s · 300 W
In short
The NVIDIA RTX 6000 Ada Generation has 48 GB of GDDR6 memory with 960 GB/s of bandwidth, which sets how fast it generates text. At 8k context it runs 68 of the 125 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q8_0, at about 20 tok/s (estimated). We have no current price for the NVIDIA RTX 6000 Ada Generation in Germany.
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.
No retailer in this market lists it right now.
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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 256k | 20tok/sest. | 717 tok/s | chat, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | fits | 40.0 GB | 256k | 97tok/sest. | 1897 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.0 GB | 256k | 20tok/sest. | 717 tok/s | chat, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | fits | 46.2 GB | 48k78k with q8 cache | 135tok/sest. | 4792 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 32.5 GB | 184k256k with q8 cache | 17tok/sest. | 625 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | fits | 38.4 GB | 332k528k with q8 cache | 139tok/sest. | 2479 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.3 GB | 256k | 108tok/sest. | 6145 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.0 GB | 256k | 20tok/sest. | 717 tok/s | chat, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.1 GB | 256k | 79tok/sest. | 4683 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q2_K | fits | 44.4 GB | 24k44k with q8 cache | 49tok/sest. | 1131 tok/s | chat, coding |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | fits | 46.2 GB | 49k79k with q8 cache | 173tok/sest. | 6024 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.3 GB | 256k | 108tok/sest. | 6145 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 30.8 GB | 198k | 62tok/sest. | 3439 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.3 GB | 144k262k with q8 cache | 23tok/sest. | 809 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 33.4 GB | 256k | 104tok/sest. | 6403 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q6_K | fits | 38.5 GB | 662k902k with q8 cache | 139tok/sest. | 5840 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.2 GB | 128k | 136tok/sest. | 4448 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 31.7 GB | 165k256k with q8 cache | 89tok/sest. | 4446 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 35.2 GB | 40k | 16tok/sest. | 553 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 13.0 GB | 256k | 45tok/sest. | 1632 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 9.9 GB | 256k | 60tok/sest. | 2066 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.3 GB | 128k | 23tok/sest. | 809 tok/s | chat |
| Gemma 3 27B | Q8_0 | fits | 28.5 GB | 128k | 20tok/sest. | 727 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 35.2 GB | 55k102k with q8 cache | 16tok/sest. | 578 tok/s | chat |
| Llama 3.3 70B Meta | Q4_K_M | fits | 42.8 GB | 22k41k with q8 cache | 13tok/sest. | 270 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 15.4 GB | 205k256k with q8 cache | 38tok/sest. | 1341 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 16.6 GB | 40k | 35tok/sest. | 1246 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.0 GB | 128k | 60tok/sest. | 2181 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.0 GB | 40k | 60tok/sest. | 2181 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 16.8 GB | 16k | 35tok/sest. | 1255 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.2 GB | 256k | 124tok/sest. | 4159 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.2 GB | 256k | 59tok/sest. | 2038 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 10.7 GB | 128k | 56tok/sest. | 2023 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 8.6 GB | 128k | 70tok/sest. | 2504 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.5 GB | 125k | 244tok/sest. | 14613 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 7.9 GB | 128k | 78tok/sest. | 2252 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.3 GB | 32k | 942tok/sest. | 30584 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 1.6 GB | 256k | 639tok/sest. | 21043 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.2 GB | 256k | 383tok/sest. | 8632 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 2.7 GB | 128k | 280tok/sest. | 9626 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 3.6 GB | 128k | 196tok/sest. | 6363 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 3.9 GB | 128k | 176tok/sest. | 6404 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 3.9 GB | 32k | 176tok/sest. | 5652 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 3.9 GB | 1024k | 175tok/sest. | 4528 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 4.7 GB | 128k | 139tok/sest. | 4239 tok/s | chat, coding, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.0 GB | 256k | 132tok/sest. | 4341 tok/s | chat, coding, agents, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 5.0 GB | 128k | 130tok/sest. | 4556 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 25.1 GB | 128k | 128tok/sest. | 7674 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 12.9 GB | 128k | 127tok/sest. | 7041 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.3 GB | 256k | 121tok/sest. | 4159 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 16.8 GB | 128k | 106tok/sest. | 5936 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 17.6 GB | 128k | 102tok/sest. | 5936 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 8.7 GB | 128k | 70tok/sest. | 2429 tok/s | chat, coding, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 8.7 GB | 32k | 69tok/sest. | 1908 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 9.7 GB | 128k | 62tok/sest. | 2252 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.2 GB | 256k | 59tok/sest. | 2038 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 10.4 GB | 128k | 58tok/sest. | 1762 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 12.0 GB | 64k | 49tok/sest. | 1762 tok/s | chat, coding, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 15.4 GB | 205k256k with q8 cache | 38tok/sest. | 1341 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 16.9 GB | 128k | 34tok/sest. | 1221 tok/s | chat, coding |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 20.6 GB | 256k | 28tok/sest. | 717 tok/s | chat, coding, long documents |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 25.3 GB | 128k | 23tok/sest. | 823 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 25.3 GB | 40k | 23tok/sest. | 823 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 25.3 GB | 40k | 23tok/sest. | 823 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 25.3 GB | 128k | 23tok/sest. | 809 tok/s | chat |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 31.0 GB | 128k | 18tok/sest. | 664 tok/s | chat, long documents |
| granite 4.2 30b IBM | Q8_0 | fits | 31.7 GB | 69k127k with q8 cache | 18tok/sest. | 652 tok/s | chat |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | fits | 42.8 GB | 22k41k with q8 cache | 13tok/sest. | 270 tok/s | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | offload | 72.8 GB | – | 14tok/sest. | 1142 tok/s | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 51.9 GB | – | 34tok/sest. | 1583 tok/s | chat, coding, agents, long documents |
| gpt-oss 120B OpenAI | Q4_K_M | offload | 59.5 GB | – | 34tok/sest. | 2819 tok/s | chat, coding |
| GLM 4.5V Z.ai | Q4_K_M | offload | 61.4 GB | – | 11tok/sest. | 933 tok/s | – |
| GLM 4.6V Z.ai | Q4_K_M | offload | 67.8 GB | – | 8tok/sest. | 886 tok/s | – |
| Kimi Dev 72B Moonshot AI | Q6_K | offload | 63.2 GB | – | 3tok/sest. | 223 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | offload | 73.3 GB | – | 2tok/sest. | 120 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | offload | 73.3 GB | – | 2tok/sest. | 118 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 91.6 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 74.5 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.4 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 377.9 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.1 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 155.8 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.4 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.2 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 383.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 747.8 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.4 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 579.9 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.0 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.4 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- RTX 6000 Ada Generation
- Memory
- 48 GB GDDR6
- Memory bus
- 384-bit
- Memory bandwidth
- 960 GB/s
- FP16 compute
- 91.1 TFLOPS
- Software
- CUDA
- Board power
- 300 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA RTX 6000 Ada Generation have for AI models?
- The NVIDIA RTX 6000 Ada Generation has 48 GB of GDDR6 memory with 960 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA RTX 6000 Ada Generation can run locally?
- Qwen 3.8 27B (Q8_0) fits fully in its memory at 8k context and generates at about 20 tok/s, an estimate from its memory bandwidth. 68 of the 125 models we track fit at that context.
- Can the NVIDIA RTX 6000 Ada Generation run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 92 GB at 8k context, more than the NVIDIA RTX 6000 Ada Generation and system RAM can hold.
- How much does the NVIDIA RTX 6000 Ada Generation cost in Germany?
- We have no current price for the NVIDIA RTX 6000 Ada Generation in Germany.
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.