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 64k context it runs 77 of the 125 open models we track fully in memory; the most capable is Qwen 3.8 Flash Next at UD-Q3_K_XL, at about 11 tok/s (estimated). We have no current price for the NVIDIA RTX 6000 Ada Generation in Canada.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Canada, 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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q3_K_XL | fits | 86.9 GB | 256k | 11tok/sest. | 309 tok/s | – |
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 32.7 GB | 256k | 18tok/sest. | 599 tok/s | chat, long documents |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | fits | 87.1 GB | 95k175k with q8 cache | 18tok/sest. | 570 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q5_K_M | fits | 88.3 GB | 256k | 39tok/sest. | 1247 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 32.2 GB | 256k | 18tok/sest. | 599 tok/s | chat, long documents |
| gpt-oss 120B OpenAI | MXFP4 | fits | 62.8 GB | 128k | 65tok/sest. | 1934 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q8_0 | fits | 82.0 GB | 256k | 62tok/sest. | 2889 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | Q5_K_M | fits | 92.1 GB | 256k | 35tok/sest. | 1449 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 37.7 GB | 256k | 15tok/sest. | 547 tok/s | chat |
| Mistral Small 4 119B Mistral AI | Q6_K | fits | 93.8 GB | 98k156k with q8 cache | 49tok/sest. | 1226 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 37.2 GB | 256k | 80tok/sest. | 3606 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 32.2 GB | 256k | 18tok/sest. | 599 tok/s | chat, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.9 GB | 256k | 63tok/sest. | 3692 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q5_K_M | fits | 90.8 GB | 85k128k with q8 cache | 16tok/sest. | 406 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 37.2 GB | 256k | 80tok/sest. | 3606 tok/s | chat, coding, agents, long documents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q8_0 | fits | 82.0 GB | 256k | 74tok/sest. | 3295 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 34.4 GB | 198k | 41tok/sest. | 1789 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 34.8 GB | 384k | 17tok/sest. | 590 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 34.5 GB | 256k | 95tok/sest. | 4446 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 50.7 GB | 1024k | 95tok/sest. | 2896 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.3 GB | 128k | 88tok/sest. | 2760 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 37.7 GB | 256k | 37tok/sest. | 1290 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 49.9 GB | 40k | 11tok/sest. | 305 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 14.6 GB | 256k | 42tok/sest. | 1419 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.4 GB | 256k | 51tok/sest. | 1737 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q8_0 | fits | 33.6 GB | 128k | 17tok/sest. | 671 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 17tok/sest. | 590 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 49.9 GB | 128k | 11tok/sest. | 378 tok/s | chat |
| Llama 3.3 70B Meta | Q8_0 | fits | 91.3 GB | 74k128k with q8 cache | 6tok/sest. | 181 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 24.8 GB | 256k | 24tok/sest. | 830 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 26.1 GB | 40k | 23tok/sest. | 727 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.6 GB | 128k | 32tok/sest. | 1148 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.6 GB | 40k | 32tok/sest. | 1148 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 28.5 GB | 16k | 21tok/sest. | 730 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.7 GB | 256k | 89tok/sest. | 3011 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.4 GB | 256k | 33tok/sest. | 1136 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 20.2 GB | 128k | 30tok/sest. | 1050 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 10.9 GB | 128k | 59tok/sest. | 2275 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.9 GB | 125k | 83tok/sest. | 4856 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.6 GB | 128k | 39tok/sest. | 1233 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 32k | 445tok/sest. | 10769 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.0 GB | 256k | 364tok/sest. | 12210 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.6 GB | 256k | 263tok/sest. | 6656 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 5.0 GB | 128k | 158tok/sest. | 4460 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.6 GB | 128k | 108tok/sest. | 2514 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.6 GB | 1024k | 108tok/sest. | 3086 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.4 GB | 128k | 98tok/sest. | 4500 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.8 GB | 256k | 87tok/sest. | 3011 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.9 GB | 128k | 86tok/sest. | 3049 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.9 GB | 32k | 86tok/sest. | 2867 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 19.2 GB | 128k | 69tok/sest. | 3095 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 20.0 GB | 128k | 67tok/sest. | 3095 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.8 GB | 128k | 66tok/sest. | 1914 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 10.1 GB | 128k | 64tok/sest. | 1977 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.4 GB | 256k | 56tok/sest. | 1893 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.7 GB | 32k | 54tok/sest. | 1018 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.5 GB | 128k | 50tok/sest. | 1444 tok/s | chat, coding, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 30.2 GB | 128k | 48tok/sest. | 2782 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.3 GB | 128k | 47tok/sest. | 975 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.9 GB | 64k | 41tok/sest. | 975 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.4 GB | 128k | 35tok/sest. | 1233 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.4 GB | 256k | 33tok/sest. | 1136 tok/s | chat, coding, agents, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 24.8 GB | 256k | 24tok/sest. | 830 tok/s | chat, coding, agents, long documents |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 24.9 GB | 256k | 24tok/sest. | 599 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 28.1 GB | 128k | 21tok/sest. | 664 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 32.5 GB | 128k | 18tok/sest. | 604 tok/s | chat, long documents |
| GLM 4.5V Z.ai | Q4_K_M | fits | 72.2 GB | 64k | 17tok/sest. | 399 tok/s | chat, coding |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 17tok/sest. | 597 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 34.8 GB | 40k | 17tok/sest. | 597 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 34.8 GB | 40k | 17tok/sest. | 597 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 17tok/sest. | 590 tok/s | chat |
| GLM 4.6V Z.ai | Q4_K_M | fits | 78.6 GB | 128k | 17tok/sest. | 399 tok/s | chat, coding |
| granite 4.2 30b IBM | Q8_0 | fits | 46.5 GB | 128k | 12tok/sest. | 441 tok/s | chat |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q8_0 | fits | 91.3 GB | 74k128k with q8 cache | 6tok/sest. | 181 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | fits | 93.2 GB | 68k127k with q8 cache | 6tok/sest. | 105 tok/s | – |
| Kimi Dev 72B Moonshot AI | Q8_0 | fits | 93.4 GB | 68k126k with q8 cache | 6tok/sest. | 177 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | fits | 93.2 GB | 68k127k with q8 cache | 6tok/sest. | 103 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | offload | 97.0 GB | 39k69k with q8 cache | 23tok/sest. | 179 tok/s | chat, coding |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | offload | 103.5 GB | – | 20tok/sest. | 264 tok/s | chat, coding |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.9 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.4 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 383.3 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 161.3 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 225.3 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 226.1 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 389.3 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.9 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.8 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 753.3 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.9 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 584.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.8 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 132.2 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.7 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?
- Qwen 3.8 Flash Next (UD-Q3_K_XL) fits fully in its memory at 64k context and generates at about 11 tok/s, an estimate from its memory bandwidth. 77 of the 125 models we track fit at that context.
- Can the NVIDIA RTX 6000 Ada Generation run DeepSeek V4 Flash?
- Not fully in memory: at UD-Q2_K_XL and 64k context DeepSeek V4 Flash needs about 97 GB, so part of it runs from system RAM and it slows to about 23 tok/s (estimated).
- How much does the NVIDIA RTX 6000 Ada Generation cost in Canada?
- We have no current price for the NVIDIA RTX 6000 Ada Generation in Canada.
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.