NVIDIA RTX PRO 4500 Blackwell
32 GB · 896 GB/s · 200 W
In short
The NVIDIA RTX PRO 4500 Blackwell has 32 GB of GDDR7 memory with 896 GB/s of bandwidth, which sets how fast it generates text. At 8k context it runs 71 of the 125 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q8_0, at about 19 tok/s (estimated). The best new price for the NVIDIA RTX PRO 4500 Blackwell in Canada is $8,900 at Amazon.
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.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| AmazonPNY NVIDIA RTX Pro 4500 Blackwell Workstation Edition | New | $8,900 | In stock | 2 h ago | Buy |
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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 28.8 GB | 256k | 19tok/sest. | 432 tok/s | chat |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q3_K_M | fits | 54.0 GB | 256k | 69tok/sest. | 1144 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 256k | 19tok/sest. | 432 tok/s | chat |
| gpt-oss 120B OpenAI | MXFP4 | fits | 60.5 GB | 64k108k with q8 cache | 97tok/sest. | 1940 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder Next Alibaba Qwen | Q6_K | fits | 62.5 GB | 17k28k with q8 cache | 96tok/sest. | 2890 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q3_K_M | fits | 58.8 GB | 256k | 54tok/sest. | 1008 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 32.9 GB | 256k | 16tok/sest. | 377 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q3_K_M | fits | 52.0 GB | 397k630k with q8 cache | 98tok/sest. | 1495 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.7 GB | 256k | 101tok/sest. | 3706 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.4 GB | 256k | 19tok/sest. | 432 tok/s | chat |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.5 GB | 256k | 73tok/sest. | 2824 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q3_K_M | fits | 55.9 GB | 45k83k with q8 cache | 38tok/sest. | 682 tok/s | chat, coding |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q6_K | fits | 62.4 GB | 20k32k with q8 cache | 124tok/sest. | 3633 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 35.7 GB | 256k | 101tok/sest. | 3706 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 31.2 GB | 198k | 58tok/sest. | 2074 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 236k384k with q8 cache | 21tok/sest. | 488 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 33.8 GB | 256k | 97tok/sest. | 3861 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.6 GB | 128k | 127tok/sest. | 2682 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 49.9 GB | 959k1024k with q8 cache | 101tok/sest. | 3522 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 32.1 GB | 256k | 83tok/sest. | 2681 tok/s | chat, coding, agents, long documents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 35.6 GB | 40k | 15tok/sest. | 334 tok/s | chat |
| Gemma 4 12B | Q8_0 | fits | 13.4 GB | 256k | 42tok/sest. | 984 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.3 GB | 256k | 56tok/sest. | 1246 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 21tok/sest. | 488 tok/s | chat |
| Gemma 3 27B | Q8_0 | fits | 28.9 GB | 128k | 19tok/sest. | 438 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 35.6 GB | 114k128k with q8 cache | 15tok/sest. | 349 tok/s | chat |
| Llama 3.3 70B Meta | Q5_K_M | fits | 50.2 GB | 47k88k with q8 cache | 11tok/sest. | 163 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 15.8 GB | 256k | 35tok/sest. | 809 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 17.0 GB | 40k | 33tok/sest. | 752 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.4 GB | 128k | 56tok/sest. | 1315 tok/s | chat, coding, long documents |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.4 GB | 40k | 56tok/sest. | 1315 tok/s | chat, coding, long documents |
| Phi-4 14B Microsoft | Q8_0 | fits | 17.2 GB | 16k | 32tok/sest. | 757 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.6 GB | 256k | 116tok/sest. | 2508 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.6 GB | 256k | 55tok/sest. | 1229 tok/s | chat, coding, long documents |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.1 GB | 128k | 52tok/sest. | 1220 tok/s | chat, coding, agents, long documents |
| Gemma 4 E4B | Q8_0 | fits | 9.0 GB | 128k | 66tok/sest. | 1510 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 9.9 GB | 125k | 227tok/sest. | 8813 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 8.3 GB | 128k | 72tok/sest. | 1358 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.7 GB | 32k | 879tok/sest. | 18445 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.0 GB | 256k | 596tok/sest. | 12690 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.6 GB | 256k | 357tok/sest. | 5205 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.1 GB | 128k | 261tok/sest. | 5805 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.0 GB | 128k | 183tok/sest. | 3837 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 4.3 GB | 128k | 164tok/sest. | 3862 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 4.3 GB | 32k | 164tok/sest. | 3408 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 4.3 GB | 1024k | 163tok/sest. | 2730 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 5.1 GB | 128k | 130tok/sest. | 2556 tok/s | chat, coding, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 5.4 GB | 256k | 123tok/sest. | 2618 tok/s | chat, coding, agents, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 5.4 GB | 128k | 122tok/sest. | 2748 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q8_0 | fits | 25.5 GB | 128k | 119tok/sest. | 4628 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.3 GB | 128k | 118tok/sest. | 4246 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 5.7 GB | 256k | 112tok/sest. | 2508 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 17.2 GB | 128k | 99tok/sest. | 3580 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 18.0 GB | 128k | 95tok/sest. | 3580 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 9.1 GB | 128k | 65tok/sest. | 1465 tok/s | chat, coding, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 9.1 GB | 32k | 65tok/sest. | 1151 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 10.1 GB | 128k | 58tok/sest. | 1358 tok/s | chat, coding, long documents |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 10.6 GB | 256k | 55tok/sest. | 1229 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 10.8 GB | 128k | 54tok/sest. | 1062 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 12.4 GB | 64k | 46tok/sest. | 1062 tok/s | chat, coding, long documents |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 15.8 GB | 256k | 35tok/sest. | 809 tok/s | chat, coding, long documents |
| GLM 4.5V Z.ai | Q4_K_M | fits | 61.8 GB | 13k24k with q8 cache | 33tok/sest. | 654 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 17.3 GB | 128k | 32tok/sest. | 737 tok/s | chat, coding |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 21.0 GB | 256k | 26tok/sest. | 432 tok/s | chat, coding, long documents |
| Devstral Small 2507 Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 21tok/sest. | 496 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q8_0 | fits | 25.7 GB | 40k | 21tok/sest. | 496 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q8_0 | fits | 25.7 GB | 40k | 21tok/sest. | 496 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q8_0 | fits | 25.7 GB | 128k | 21tok/sest. | 488 tok/s | chat |
| Muse Glimmer 30B meta-models | Q8_0 | fits | 31.4 GB | 128k | 17tok/sest. | 401 tok/s | chat, long documents |
| granite 4.2 30b IBM | Q8_0 | fits | 32.1 GB | 127k128k with q8 cache | 17tok/sest. | 393 tok/s | chat |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q5_K_M | fits | 50.2 GB | 47k88k with q8 cache | 11tok/sest. | 163 tok/s | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | offload | 74.9 GB | – | 5tok/sest. | 179 tok/s | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | offload | 73.2 GB | – | 25tok/sest. | 798 tok/s | chat |
| GLM 4.6V Z.ai | Q4_K_M | offload | 68.2 GB | – | 18tok/sest. | 622 tok/s | chat |
| Kimi Dev 72B Moonshot AI | Q6_K | offload | 63.6 GB | 5k10k with q8 cache | 7tok/sest. | 157 tok/s | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | offload | 73.7 GB | – | 3tok/sest. | 84 tok/s | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | offload | 73.7 GB | – | 3tok/sest. | 82 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 92.0 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.6 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 378.8 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 378.3 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 379.2 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 147.5 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 156.2 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 204.8 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 205.6 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 384.2 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 421.8 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 435.7 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 748.2 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 579.8 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 580.3 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 131.9 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 118.4 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 241.8 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- RTX PRO 4500 Blackwell
- Memory
- 32 GB GDDR7
- Memory bus
- 256-bit
- Memory bandwidth
- 896 GB/s
- FP16 compute
- 54.94 TFLOPS
- Software
- CUDA
- Board power
- 200 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the NVIDIA RTX PRO 4500 Blackwell have for AI models?
- The NVIDIA RTX PRO 4500 Blackwell has 32 GB of GDDR7 memory with 896 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the NVIDIA RTX PRO 4500 Blackwell can run locally?
- Qwen 3.8 27B (Q8_0) fits fully in its memory at 8k context and generates at about 19 tok/s, an estimate from its memory bandwidth. 71 of the 125 models we track fit at that context.
- Can the NVIDIA RTX PRO 4500 Blackwell 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 PRO 4500 Blackwell and system RAM can hold.
- How much does the NVIDIA RTX PRO 4500 Blackwell cost in Canada?
- The best new price for the NVIDIA RTX PRO 4500 Blackwell in Canada is $8,900 at Amazon.
Speeds on this page are for 8k context. See the best hardware for local AI at every budget.