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 128k 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 22 tok/s (estimated). We have no current price for the NVIDIA RTX PRO 5000 Blackwell 72GB in the US.
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in the US, 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 @128k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 36.6 GB | 256k | 22tok/sest. | 408 tok/s | chat, coding, long documents |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q3_K_M | fits | 57.1 GB | 256k | 63tok/sest. | 725 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 36.2 GB | 256k | 22tok/sest. | 408 tok/s | chat, coding, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q6_K | fits | 65.6 GB | 256k | 77tok/sest. | 1607 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q3_K_M | fits | 60.1 GB | 256k | 69tok/sest. | 1018 tok/s | chat, coding, agents, long documents |
| gpt-oss 120B OpenAI | MXFP4 | fits | 65.0 GB | 128k | 63tok/sest. | 1074 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 42.6 GB | 256k | 19tok/sest. | 387 tok/s | chat, coding, long documents |
| Mistral Small 4 119B Mistral AI | MXFP4 | fits | 71.1 GB | 137k217k with q8 cache | 69tok/sest. | 628 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 38.4 GB | 256k | 86tok/sest. | 1981 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 36.2 GB | 256k | 22tok/sest. | 408 tok/s | chat, coding, long documents |
| Gemma 4 26B-A4B | Q8_0 | fits | 29.2 GB | 256k | 71tok/sest. | 2405 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q2_K | fits | 66.7 GB | 128k | 16tok/sest. | 189 tok/s | chat, coding, agents |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q6_K | fits | 65.6 GB | 256k | 88tok/sest. | 1756 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 38.4 GB | 256k | 86tok/sest. | 1981 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 37.7 GB | 198k | 40tok/sest. | 935 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 44.8 GB | 292k384k with q8 cache | 18tok/sest. | 365 tok/s | chat, coding, long documents |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 34.8 GB | 256k | 120tok/sest. | 2665 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 51.1 GB | 1024k | 117tok/sest. | 1487 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 15.7 GB | 128k | 89tok/sest. | 1557 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 43.7 GB | 256k | 31tok/sest. | 576 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 65.9 GB | 40k | 12tok/sest. | 163 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 15.6 GB | 256k | 55tok/sest. | 999 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 14.4 GB | 256k | 60tok/sest. | 1189 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q8_0 | fits | 38.6 GB | 128k | 21tok/sest. | 499 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 44.8 GB | 128k | 18tok/sest. | 365 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 65.9 GB | 128k | 12tok/sest. | 219 tok/s | chat |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 34.8 GB | 256k | 23tok/sest. | 468 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 36.1 GB | 40k | 22tok/sest. | 399 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 27.6 GB | 128k | 30tok/sest. | 603 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 27.6 GB | 40k | 30tok/sest. | 603 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 41.0 GB | 16k | 20tok/sest. | 400 tok/s | chat, coding, long documents |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 9.7 GB | 256k | 94tok/sest. | 1852 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 26.9 GB | 256k | 31tok/sest. | 610 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 30.2 GB | 128k | 27tok/sest. | 548 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 12.6 GB | 128k | 70tok/sest. | 1667 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 15.8 GB | 125k | 67tok/sest. | 2228 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 23.6 GB | 128k | 35tok/sest. | 658 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 3.4 GB | 32k | 389tok/sest. | 5005 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.7 GB | 256k | 341tok/sest. | 6675 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 4.3 GB | 256k | 272tok/sest. | 4268 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 6.7 GB | 128k | 147tok/sest. | 2236 tok/s | chat, coding, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 15.3 GB | 128k | 109tok/sest. | 2577 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 8.8 GB | 1024k | 105tok/sest. | 1831 tok/s | chat, coding, agents, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 9.2 GB | 128k | 100tok/sest. | 1202 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 9.8 GB | 256k | 93tok/sest. | 1852 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 11.6 GB | 128k | 76tok/sest. | 1542 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 11.6 GB | 32k | 76tok/sest. | 1484 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 21.1 GB | 128k | 70tok/sest. | 1618 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 21.8 GB | 128k | 68tok/sest. | 1618 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 14.1 GB | 32k | 61tok/sest. | 537 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 14.8 GB | 128k | 58tok/sest. | 952 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 15.1 GB | 128k | 57tok/sest. | 971 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 15.8 GB | 128k | 54tok/sest. | 522 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 16.0 GB | 128k | 53tok/sest. | 798 tok/s | chat, coding, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 17.4 GB | 64k | 49tok/sest. | 522 tok/s | chat, coding, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 17.9 GB | 256k | 47tok/sest. | 931 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 35.2 GB | 128k | 39tok/sest. | 1302 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 25.4 GB | 128k | 32tok/sest. | 658 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 26.9 GB | 256k | 31tok/sest. | 610 tok/s | chat, coding, agents, long documents |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 28.8 GB | 256k | 28tok/sest. | 408 tok/s | chat, coding, agents, long documents |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 33.3 GB | 128k | 24tok/sest. | 443 tok/s | chat, coding, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 34.8 GB | 256k | 23tok/sest. | 468 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 40.1 GB | 128k | 20tok/sest. | 353 tok/s | chat, coding, long documents |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 44.8 GB | 128k | 18tok/sest. | 368 tok/s | chat, coding, long documents |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 44.8 GB | 40k | 18tok/sest. | 368 tok/s | chat, coding, long documents |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 44.8 GB | 40k | 18tok/sest. | 368 tok/s | chat, coding, long documents |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 44.8 GB | 128k | 18tok/sest. | 365 tok/s | chat, coding, long documents |
| granite 4.2 30b IBM | Q8_0 | fits | 62.4 GB | 128k | 13tok/sest. | 261 tok/s | chat, coding |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | offload | 78.0 GB | – | 7tok/sest. | 221 tok/s | – |
| Llama 3.3 70B Meta | Q4_K_M | offload | 81.1 GB | 97k128k with q8 cache | 4tok/sest. | 98 tok/s | chat |
| GLM 4.5V Z.ai | Q4_K_M | offload | 83.7 GB | 61k64k with q8 cache | 5tok/sest. | 171 tok/s | chat, coding, agents |
| GLM 4.6V Z.ai | Q4_K_M | offload | 90.1 GB | 27k50k with q8 cache | 4tok/sest. | 164 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | offload | 81.1 GB | 97k128k with q8 cache | 4tok/sest. | 98 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 102.4 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 104.2 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 102.6 GB | 2k4k with q8 cache | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 387.2 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 386.7 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 387.6 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 157.8 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 166.6 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 115.2 GB | 2k5k with q8 cache | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 248.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 249.0 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 394.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 432.4 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 446.3 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 758.7 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 101.4 GB | 33k62k with q8 cache | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 588.2 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 588.6 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 161.3 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 147.7 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 256.1 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 115.2 GB | 2k5k with q8 cache | – | – | – |
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?
- Qwen 3.8 27B (Q8_0) fits fully in its memory at 128k context and generates at about 22 tok/s, an estimate from its memory bandwidth. 68 of the 125 models we track fit at that context.
- Can the NVIDIA RTX PRO 5000 Blackwell 72GB run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 102 GB at 128k context, more than the NVIDIA RTX PRO 5000 Blackwell 72GB and system RAM can hold.
- How much does the NVIDIA RTX PRO 5000 Blackwell 72GB cost in the US?
- We have no current price for the NVIDIA RTX PRO 5000 Blackwell 72GB in the US.
Speeds on this page are for 128k context. See the best hardware for local AI at every budget.