readygpu

NVIDIA RTX 6000 Ada Generation vs NVIDIA RTX PRO 5000 Blackwell 72GB

For running models locally, priced in Canada. At 128k context the first runs 60 models fully in memory, the second 68.

In short

The NVIDIA RTX PRO 5000 Blackwell 72GB has more memory for models: 72 GB against 48 GB. At 128k context the NVIDIA RTX PRO 5000 Blackwell 72GB runs 68 of the models we track fully in memory and the NVIDIA RTX 6000 Ada Generation 60; only the NVIDIA RTX PRO 5000 Blackwell 72GB holds Qwen3 Coder Next. On the models both run fully in memory, the NVIDIA RTX PRO 5000 Blackwell 72GB is about 1.4× as fast as the NVIDIA RTX 6000 Ada Generation (estimated, median across models).

Updated . Speeds are estimates; how they are worked out.

NVIDIA RTX 6000 Ada Generation

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NVIDIA RTX PRO 5000 Blackwell 72GB

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Specifications

SpecNVIDIA RTX 6000 Ada GenerationNVIDIA RTX PRO 5000 Blackwell 72GB
GPURTX 6000 Ada GenerationRTX PRO 5000 Blackwell 72GB
Memory48 GB GDDR672 GB GDDR7
Memory bus384-bit384-bit
Memory bandwidth960 GB/s1,344 GB/s
FP16 compute91.1 TFLOPS73.69 TFLOPS
SoftwareCUDACUDA
Board power300 W300 W
PCIe generationGen 4Gen 5
PCIe lanesx16x16

What each runs

Estimated decode speed with the most precise quant that fits each one est.

ModelNVIDIA RTX 6000 Ada GenerationNVIDIA RTX PRO 5000 Blackwell 72GB
Qwen 3.8 27B16tok/sQ8_022tok/sQ8_0
Qwen 3.5 122B-A10B53tok/sUD-Q2_K_XL63tok/sQ3_K_M
Qwen 3.6 27B16tok/sQ8_022tok/sQ8_0
Gemma 4 31B14tok/sQ8_019tok/sQ8_0
Qwen3 Coder Nextoffload77tok/sQ6_K
Nemotron 3 Super 120B-A12Boffload69tok/sUD-Q3_K_M
gpt-oss 120Boffload63tok/sMXFP4
Mistral Small 4 119B66tok/sUD-Q2_K_XL69tok/sMXFP4
Qwen 3.6 35B-A3B61tok/sQ8_086tok/sQ8_0
Qwen 3.5 27B16tok/sQ8_022tok/sQ8_0
Gemma 4 26B-A4B51tok/sQ8_071tok/sQ8_0
GLM 4.5 Airoffload16tok/sQ2_K
Qwen 3.5 35B-A3B61tok/sQ8_086tok/sQ8_0
GLM 4.7 Flash29tok/sQ8_040tok/sQ8_0
Devstral Small 2 24B13tok/sQ8_018tok/sQ8_0
Qwen3 Next 80B-A3Boffload88tok/sQ6_K
Nemotron 3.5 Lightning 30B-A3B86tok/sUD-Q6_K_XL120tok/sUD-Q6_K_XL
Kimi Linear 48B-A3B100tok/sQ6_K117tok/sQ8_0
gpt-oss 20B63tok/sMXFP489tok/sMXFP4
Qwen3 Coder 30B-A3B22tok/sQ8_031tok/sQ8_0
Qwen3 32Boffload12tok/sQ8_0
Gemma 4 12B39tok/sQ8_055tok/sQ8_0
Qwen 3.5 9B43tok/sQ8_060tok/sQ8_0
Gemma 3 27B15tok/sQ8_021tok/sQ8_0
Mistral Small 3.2 24B13tok/sQ8_018tok/sQ8_0
DeepSeek R1 Distill Qwen 32Boffload12tok/sQ8_0
Ministral 3 14B17tok/sQ8_023tok/sQ8_0
Qwen3 14B16tok/sQ8_022tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B21tok/sQ8_030tok/sQ8_0
Qwen3 8B21tok/sQ8_030tok/sQ8_0
Phi-4 14B14tok/sQ8_020tok/sQ8_0
Qwen 3.5 4B67tok/sQ8_094tok/sQ8_0
Ministral 3 8B22tok/sQ8_031tok/sQ8_0
Granite 4.2 8B19tok/sQ8_027tok/sQ8_0
Gemma 4 E4B50tok/sQ8_070tok/sQ8_0
LFM2.5 8B-A1B48tok/sQ8_067tok/sQ8_0
Llama 3.1 8B25tok/sQ6_K35tok/sQ6_K
Qwen2.5 0.5B278tok/sQ8_0389tok/sQ8_0
Qwen3.5 0.8B244tok/sQ8_0341tok/sQ8_0
Qwen3.5 2B194tok/sQ5_K_M272tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B105tok/sQ8_0147tok/sQ8_0
Mellum2.1 12B A2.5B Thinking78tok/sQ8_0109tok/sQ8_0
Spark X2.5 4B75tok/smlx-4bit105tok/smlx-4bit
MiniCPM5 2B72tok/sQ8_0100tok/sQ8_0
FrogNano 4B 260966tok/sQ8_093tok/sQ8_0
LFM2.5 2.6B55tok/sQ8_076tok/sQ8_0
LFM2.5 VL 3B55tok/sQ8_076tok/sQ8_0
Kimi VL A3B Thinking 250650tok/sQ8_070tok/sQ8_0
Kimi VL A3B49tok/smlx-8bit68tok/smlx-8bit
GLM 4 9B 041444tok/smlx-5bit61tok/smlx-5bit
granite vision 4.1 4b42tok/sQ8_058tok/sQ8_0
granite 4.2 3b41tok/sQ8_057tok/sQ8_0
GLM 4.6V Flash39tok/sQ8_054tok/sQ8_0
DeepSeek R1 Distill Qwen 7B38tok/sQ8_053tok/sQ8_0
GLM 4.1V 9B Thinking35tok/smlx-8bit49tok/smlx-8bit
Ministral 3 3B Instruct 251234tok/sQ8_047tok/sQ8_0
LFM2.5 24B A2B28tok/sQ8_039tok/sQ8_0
DeepSeek R1 Distill Llama 8B23tok/sQ8_032tok/sQ8_0
Ministral 3 8B Reasoning 251222tok/sQ8_031tok/sQ8_0
Qwen3.8 27B OBLITERATED20tok/smlx-4bit28tok/smlx-4bit
Muse Glimmer 30B17tok/sQ8_024tok/sQ8_0
Ministral 3 14B Reasoning 251217tok/sQ8_023tok/sQ8_0
DeepSeek R1 Distill Qwen 14B14tok/sQ8_020tok/sQ8_0
Devstral Small 250713tok/sQ8_018tok/sQ8_0
Magistral Small 250613tok/sQ8_018tok/sQ8_0
Magistral Small 250713tok/sQ8_018tok/sQ8_0
Magistral Small 250913tok/sQ8_018tok/sQ8_0
granite 4.2 30boffload13tok/sQ8_0
Qwen 3.8 Flash Nextwon't runoffload
Llama 3.3 70Bwon't runoffload
DeepSeek R1 Distill Llama 70Bwon't runoffload
GLM 4.5Vwon't runoffload
GLM 4.6Vwon't runoffload
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon't runwon't run
MiniMax M2.7won't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek R1 Zerowon't runwon't run
DeepSeek V3won't runwon't run
DeepSeek V3 0324won't runwon't run
DeepSeek V3.1won't runwon't run
DeepSeek V3.1 Terminuswon't runwon't run
DeepSeek V3.2won't runwon't run
DeepSeek V4 Flash 0731won't runwon't run
DeepSeek V4 Flash Vision Expwon't runwon't run
Devstral 2 123B Instruct 2512won't runwon't run
GLM 4.5won't runwon't run
GLM 4.6won't runwon't run
GLM 4.7won't runwon't run
GLM 5won't runwon't run
GLM 5.1won't runwon't run
GLM 5.2won't runwon't run
GLM 5.3won't runwon't run
Kimi Dev 72Bwon't runwon't run
Kimi K2won't runwon't run
Kimi K2 Instruct 0905won't runwon't run
Kimi K2 Thinkingwon't runwon't run
Kimi K2.5won't runwon't run
MiniMax M2won't runwon't run
MiniMax M2.1won't runwon't run
MiniMax M2.5won't runwon't run
MiniMax M3won't runwon't run
Mistral Medium 3.5 128Bwon't runwon't run

Questions

Which is better for local AI, the NVIDIA RTX 6000 Ada Generation or the NVIDIA RTX PRO 5000 Blackwell 72GB?
Choose the NVIDIA RTX PRO 5000 Blackwell 72GB to run bigger models. Choose the NVIDIA RTX PRO 5000 Blackwell 72GB for speed.
Which can run bigger models, the NVIDIA RTX 6000 Ada Generation or the NVIDIA RTX PRO 5000 Blackwell 72GB?
At 128k context the NVIDIA RTX PRO 5000 Blackwell 72GB runs 68 of the models we track fully in memory and the NVIDIA RTX 6000 Ada Generation 60; only the NVIDIA RTX PRO 5000 Blackwell 72GB holds Qwen3 Coder Next.
Which is faster for local AI, the NVIDIA RTX 6000 Ada Generation or the NVIDIA RTX PRO 5000 Blackwell 72GB?
On the models both run fully in memory, the NVIDIA RTX PRO 5000 Blackwell 72GB is about 1.4× as fast as the NVIDIA RTX 6000 Ada Generation (estimated, median across models).

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