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 32k context it runs 78 of the 125 open models we track fully in memory; the most capable is DeepSeek V4 Flash at UD-Q2_K_XL, at about 37 tok/s (estimated). We have no current price for the NVIDIA RTX 6000 Ada Generation in the UK.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the UK, cheapest first. Buy links may earn us a commission.
No retailer in this market lists it right now.
What two of them run
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 |
|---|---|---|---|---|---|---|---|
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | fits | 94.2 GB | 39k69k with q8 cache | 37tok/sest. | 308 tok/s | chat, coding |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q3_K_XL | fits | 85.9 GB | 256k | 11tok/sest. | 320 tok/s | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | fits | 79.2 GB | 95k175k with q8 cache | 30tok/sest. | 872 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 30.5 GB | 256k | 19tok/sest. | 661 tok/s | chat, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q5_K_M | fits | 87.4 GB | 256k | 43tok/sest. | 1550 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 30.1 GB | 256k | 19tok/sest. | 661 tok/s | chat, long documents |
| gpt-oss 120B OpenAI | MXFP4 | fits | 61.5 GB | 128k | 82tok/sest. | 2504 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q8_0 | fits | 81.1 GB | 256k | 71tok/sest. | 3737 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | Q5_K_M | fits | 91.7 GB | 256k | 36tok/sest. | 1568 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 35.0 GB | 256k | 17tok/sest. | 589 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q6_K | fits | 94.6 GB | 39k62k with q8 cache | 54tok/sest. | 1724 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 36.3 GB | 256k | 94tok/sest. | 4721 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 30.1 GB | 256k | 19tok/sest. | 661 tok/s | chat, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.1 GB | 256k | 71tok/sest. | 4200 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q5_K_M | fits | 84.8 GB | 85k128k with q8 cache | 21tok/sest. | 640 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 36.3 GB | 256k | 94tok/sest. | 4721 tok/s | chat, coding, agents, long documents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q8_0 | fits | 81.1 GB | 256k | 89tok/sest. | 4446 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 32.6 GB | 198k | 51tok/sest. | 2465 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 29.6 GB | 384k | 20tok/sest. | 698 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 34.1 GB | 256k | 100tok/sest. | 5387 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.3 GB | 128k | 110tok/sest. | 3524 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 50.2 GB | 1024k | 102tok/sest. | 4068 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 34.5 GB | 256k | 56tok/sest. | 2171 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 41.7 GB | 40k | 14tok/sest. | 410 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 13.9 GB | 256k | 44tok/sest. | 1533 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 11.2 GB | 256k | 56tok/sest. | 1911 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 29.6 GB | 128k | 20tok/sest. | 698 tok/s | chat |
| Gemma 3 27B | Q8_0 | fits | 30.9 GB | 128k | 19tok/sest. | 702 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 41.7 GB | 128k | 14tok/sest. | 471 tok/s | chat |
| Llama 3.3 70B Meta | Q8_0 | fits | 81.1 GB | 74k128k with q8 cache | 7tok/sest. | 223 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 19.7 GB | 256k | 30tok/sest. | 1061 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 20.9 GB | 40k | 28tok/sest. | 954 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.9 GB | 128k | 44tok/sest. | 1574 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.9 GB | 40k | 44tok/sest. | 1574 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 22.0 GB | 16k | 27tok/sest. | 959 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.5 GB | 256k | 106tok/sest. | 3575 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.9 GB | 256k | 44tok/sest. | 1520 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 15.0 GB | 128k | 41tok/sest. | 1448 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 9.8 GB | 128k | 65tok/sest. | 2400 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 11.2 GB | 125k | 134tok/sest. | 7852 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.4 GB | 128k | 55tok/sest. | 1663 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.2 GB | 32k | 637tok/sest. | 17100 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.4 GB | 256k | 483tok/sest. | 16063 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.0 GB | 256k | 321tok/sest. | 7658 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.9 GB | 128k | 210tok/sest. | 6433 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 5.1 GB | 128k | 146tok/sest. | 3842 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 5.3 GB | 1024k | 138tok/sest. | 3773 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.8 GB | 128k | 122tok/sest. | 4352 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.8 GB | 32k | 122tok/sest. | 3990 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.8 GB | 128k | 113tok/sest. | 5669 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 6.6 GB | 256k | 104tok/sest. | 3575 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 7.2 GB | 128k | 94tok/sest. | 2788 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 7.4 GB | 128k | 91tok/sest. | 2922 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 18.0 GB | 128k | 87tok/sest. | 4260 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 18.8 GB | 128k | 84tok/sest. | 4260 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 7.9 GB | 256k | 83tok/sest. | 2793 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 27.5 GB | 128k | 74tok/sest. | 4376 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 10.2 GB | 32k | 62tok/sest. | 1388 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.6 GB | 128k | 60tok/sest. | 1880 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.9 GB | 128k | 53tok/sest. | 1309 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 13.2 GB | 128k | 46tok/sest. | 1663 tok/s | chat, coding, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.5 GB | 64k | 45tok/sest. | 1309 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.9 GB | 256k | 44tok/sest. | 1520 tok/s | chat, coding, agents, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 19.7 GB | 256k | 30tok/sest. | 1061 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 21.9 GB | 128k | 27tok/sest. | 898 tok/s | chat, coding |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 22.7 GB | 256k | 26tok/sest. | 661 tok/s | chat, coding, long documents |
| GLM 4.5V Z.ai | Q4_K_M | fits | 66.3 GB | 64k | 24tok/sest. | 625 tok/s | chat, coding |
| GLM 4.6V Z.ai | Q4_K_M | fits | 72.6 GB | 128k | 23tok/sest. | 625 tok/s | chat, coding |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 29.6 GB | 128k | 20tok/sest. | 708 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 29.6 GB | 40k | 20tok/sest. | 708 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 29.6 GB | 40k | 20tok/sest. | 708 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 29.6 GB | 128k | 20tok/sest. | 698 tok/s | chat |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 31.9 GB | 128k | 18tok/sest. | 637 tok/s | chat, long documents |
| granite 4.2 30b IBM | Q8_0 | fits | 38.3 GB | 128k | 15tok/sest. | 541 tok/s | chat |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q8_0 | fits | 81.1 GB | 74k128k with q8 cache | 7tok/sest. | 223 tok/s | – |
| Kimi Dev 72B Moonshot AI | Q8_0 | fits | 83.2 GB | 68k126k with q8 cache | 7tok/sest. | 218 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q5_K_M | fits | 94.5 GB | 32k60k with q8 cache | 6tok/sest. | 128 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q5_K_M | fits | 94.5 GB | 32k60k with q8 cache | 6tok/sest. | 126 tok/s | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | offload | 103.0 GB | – | 22tok/sest. | 394 tok/s | chat, coding |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.6 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 380.1 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 381.0 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.6 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.4 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 214.4 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 213.6 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.4 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 386.4 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 424.0 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.9 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.4 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.6 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 582.0 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.9 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.9 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 124.3 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 244.7 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?
- DeepSeek V4 Flash (UD-Q2_K_XL) fits fully in its memory at 32k context and generates at about 37 tok/s, an estimate from its memory bandwidth. 78 of the 125 models we track fit at that context.
- Can the NVIDIA RTX 6000 Ada Generation run GLM 5.3 Flash?
- Not fully in memory: at UD-Q2_K_XL and 32k context GLM 5.3 Flash needs about 103 GB, so part of it runs from system RAM and it slows to about 22 tok/s (estimated).
- How much does the NVIDIA RTX 6000 Ada Generation cost in the UK?
- We have no current price for the NVIDIA RTX 6000 Ada Generation in the UK.
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.