NVIDIA RTX PRO 5000 Blackwell 72GB
72 GB · 1,344 GB/s · 300 W
In short
The NVIDIA RTX PRO 5000 Blackwell 72GB has 72 GB of GDDR7 memory with 1,344 GB/s of bandwidth, which sets how fast it generates text. At 64k context it runs 80 of the 125 open models we track fully in memory; the most capable is DeepSeek V4 Flash at UD-Q3_K_M, at about 34 tok/s (estimated). We have no current price for the NVIDIA RTX PRO 5000 Blackwell 72GB 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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| DeepSeek V4 Flash DeepSeek | UD-Q3_K_M | fits | 126.1 GB | 249k444k with q8 cache | 34tok/sest. | 147 tok/s | chat, coding |
| GLM 5.3 Flash Z.ai | UD-Q3_K_XL | fits | 139.7 GB | 250k359k with q8 cache | 40tok/sest. | 225 tok/s | chat, coding |
| Qwen 3.8 Flash Next Alibaba Qwen | Q5_K_M | fits | 128.5 GB | 256k | 11tok/sest. | 250 tok/s | – |
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 32.7 GB | 256k | 25tok/sest. | 485 tok/s | chat, coding, long documents |
| MiniMax M2.7 MiniMax | UD-Q3_K_M | fits | 111.3 GB | 191k200k with q8 cache | 23tok/sest. | 461 tok/s | chat, coding, agents |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q8_0 | fits | 124.1 GB | 256k | 41tok/sest. | 1008 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 32.2 GB | 256k | 25tok/sest. | 485 tok/s | chat, coding, long documents |
| gpt-oss 120B OpenAI | MXFP4 | fits | 62.8 GB | 128k | 90tok/sest. | 1564 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q8_0 | fits | 82.0 GB | 256k | 86tok/sest. | 2337 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | Q8_0 | fits | 121.8 GB | 256k | 38tok/sest. | 1172 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 37.7 GB | 256k | 22tok/sest. | 442 tok/s | chat, coding, long documents |
| Mistral Small 4 119B Mistral AI | Q8_0 | fits | 120.7 GB | 859k1024k with q8 cache | 56tok/sest. | 991 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 37.2 GB | 256k | 112tok/sest. | 2917 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 32.2 GB | 256k | 25tok/sest. | 485 tok/s | chat, coding, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.9 GB | 256k | 88tok/sest. | 2986 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q8_0 | fits | 122.4 GB | 128k | 18tok/sest. | 328 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 37.2 GB | 256k | 112tok/sest. | 2917 tok/s | chat, coding, agents, long documents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q8_0 | fits | 82.0 GB | 256k | 104tok/sest. | 2665 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 34.4 GB | 198k | 57tok/sest. | 1447 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 34.8 GB | 384k | 23tok/sest. | 477 tok/s | chat, coding, long documents |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 34.5 GB | 256k | 132tok/sest. | 3596 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 50.7 GB | 1024k | 133tok/sest. | 2343 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.3 GB | 128k | 124tok/sest. | 2232 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 37.7 GB | 256k | 52tok/sest. | 1044 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 49.9 GB | 40k | 16tok/sest. | 247 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 14.6 GB | 256k | 59tok/sest. | 1148 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.4 GB | 256k | 71tok/sest. | 1405 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q8_0 | fits | 33.6 GB | 128k | 24tok/sest. | 543 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 23tok/sest. | 477 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 49.9 GB | 128k | 16tok/sest. | 306 tok/s | chat |
| Llama 3.3 70B Meta | Q8_0 | fits | 91.3 GB | 128k | 9tok/sest. | 146 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 24.8 GB | 256k | 33tok/sest. | 672 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 26.1 GB | 40k | 32tok/sest. | 588 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.6 GB | 128k | 45tok/sest. | 929 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.6 GB | 40k | 45tok/sest. | 929 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 28.5 GB | 16k | 29tok/sest. | 590 tok/s | chat, coding, long documents |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.7 GB | 256k | 125tok/sest. | 2436 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.4 GB | 256k | 46tok/sest. | 919 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 20.2 GB | 128k | 42tok/sest. | 849 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 10.9 GB | 128k | 82tok/sest. | 1840 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.9 GB | 125k | 117tok/sest. | 3928 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.6 GB | 128k | 55tok/sest. | 998 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 32k | 624tok/sest. | 8711 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.0 GB | 256k | 509tok/sest. | 9877 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.6 GB | 256k | 369tok/sest. | 5384 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 5.0 GB | 128k | 221tok/sest. | 3608 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.6 GB | 128k | 152tok/sest. | 2033 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.6 GB | 1024k | 151tok/sest. | 2497 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.4 GB | 128k | 137tok/sest. | 3640 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.8 GB | 256k | 122tok/sest. | 2436 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.9 GB | 128k | 121tok/sest. | 2466 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.9 GB | 32k | 121tok/sest. | 2319 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 19.2 GB | 128k | 97tok/sest. | 2503 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 20.0 GB | 128k | 94tok/sest. | 2503 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.8 GB | 128k | 93tok/sest. | 1548 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 10.1 GB | 128k | 90tok/sest. | 1599 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.4 GB | 256k | 78tok/sest. | 1531 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.7 GB | 32k | 76tok/sest. | 823 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.5 GB | 128k | 70tok/sest. | 1168 tok/s | chat, coding, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 30.2 GB | 128k | 67tok/sest. | 2250 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.3 GB | 128k | 66tok/sest. | 788 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.9 GB | 64k | 58tok/sest. | 788 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.4 GB | 128k | 49tok/sest. | 998 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.4 GB | 256k | 46tok/sest. | 919 tok/s | chat, coding, agents, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 24.8 GB | 256k | 33tok/sest. | 672 tok/s | chat, coding, agents, long documents |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 24.9 GB | 256k | 33tok/sest. | 485 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 28.1 GB | 128k | 29tok/sest. | 537 tok/s | chat, coding, long documents |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 32.5 GB | 128k | 25tok/sest. | 489 tok/s | chat, coding, long documents |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 23tok/sest. | 483 tok/s | chat, coding, long documents |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 34.8 GB | 40k | 23tok/sest. | 483 tok/s | chat, coding, long documents |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 34.8 GB | 40k | 23tok/sest. | 483 tok/s | chat, coding, long documents |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 34.8 GB | 128k | 23tok/sest. | 477 tok/s | chat, coding, long documents |
| MiniMax M2.5 MiniMax | MXFP4 | fits | 132.2 GB | 106k192k with q8 cache | 22tok/sest. | 460 tok/s | chat, coding, agents |
| GLM 4.5V Z.ai | Q8_0 | fits | 118.8 GB | 64k | 18tok/sest. | 323 tok/s | chat, coding |
| GLM 4.6V Z.ai | Q8_0 | fits | 118.8 GB | 128k | 18tok/sest. | 323 tok/s | chat, coding |
| granite 4.2 30b IBM | Q8_0 | fits | 46.5 GB | 128k | 17tok/sest. | 357 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q8_0 | fits | 91.3 GB | 128k | 9tok/sest. | 146 tok/s | – |
| Kimi Dev 72B Moonshot AI | Q8_0 | fits | 93.4 GB | 128k | 8tok/sest. | 143 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q6_K | fits | 119.0 GB | 132k244k with q8 cache | 7tok/sest. | 85 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q6_K | fits | 119.0 GB | 132k244k with q8 cache | 7tok/sest. | 84 tok/s | – |
| MiniMax M2 MiniMax | Q4_K_M | offload | 145.8 GB | 51k95k with q8 cache | 17tok/sest. | 455 tok/s | chat, coding, agents |
| MiniMax M2.1 MiniMax | Q4_K_M | offload | 145.8 GB | 51k95k with q8 cache | 17tok/sest. | 455 tok/s | chat, coding, agents |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | offload | 152.5 GB | – | 11tok/sest. | 127 tok/s | chat |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | offload | 161.3 GB | – | 8tok/sest. | 122 tok/s | – |
| 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 | – | – | – | – |
| 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 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 PRO 5000 Blackwell 72GB
- Memory
- 72 GB GDDR7
- Memory bus
- 384-bit
- Memory bandwidth
- 1,344 GB/s
- FP16 compute
- 73.69 TFLOPS
- Software
- CUDA
- Board power
- 300 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA RTX PRO 5000 Blackwell 72GB have for AI models?
- The NVIDIA RTX PRO 5000 Blackwell 72GB has 72 GB of GDDR7 memory with 1,344 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA RTX PRO 5000 Blackwell 72GB can run locally?
- DeepSeek V4 Flash (UD-Q3_K_M) fits fully in its memory at 64k context and generates at about 34 tok/s, an estimate from its memory bandwidth. 80 of the 125 models we track fit at that context.
- Can the NVIDIA RTX PRO 5000 Blackwell 72GB run MiniMax M2?
- Not fully in memory: at Q4_K_M and 64k context MiniMax M2 needs about 146 GB, so part of it runs from system RAM and it slows to about 17 tok/s (estimated).
- How much does the NVIDIA RTX PRO 5000 Blackwell 72GB cost in the UK?
- We have no current price for the NVIDIA RTX PRO 5000 Blackwell 72GB in the UK.
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.