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NVIDIA GeForce RTX 5070 Ti vs NVIDIA RTX PRO 5000 Blackwell 48GB

For running models locally, priced in the UK. At 8k context the first runs 43 models fully in memory, the second 68.

In short

The NVIDIA RTX PRO 5000 Blackwell 48GB has more memory for models: 48 GB against 16 GB. At 8k context the NVIDIA RTX PRO 5000 Blackwell 48GB runs 68 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 43; only the NVIDIA RTX PRO 5000 Blackwell 48GB holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA RTX PRO 5000 Blackwell 48GB is about 1.5× as fast as the NVIDIA GeForce RTX 5070 Ti (estimated, median across models).

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

NVIDIA GeForce RTX 5070 Ti

£975

eBay

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NVIDIA RTX PRO 5000 Blackwell 48GB

Not priced here

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Specifications

SpecNVIDIA GeForce RTX 5070 TiNVIDIA RTX PRO 5000 Blackwell 48GB
GPUGeForce RTX 5070 TiRTX PRO 5000 Blackwell 48GB
Memory16 GB GDDR748 GB GDDR7
Memory bus256-bit384-bit
Memory bandwidth896 GB/s1,344 GB/s
FP16 compute88 TFLOPS73.69 TFLOPS
SoftwareCUDACUDA
Board power300 W300 W
PCIe generationGen 5Gen 5
PCIe lanesx16x16

What each runs

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

ModelNVIDIA GeForce RTX 5070 TiNVIDIA RTX PRO 5000 Blackwell 48GB
Qwen 3.8 27Boffload28tok/sQ8_0
Qwen 3.5 122B-A10Boffload135tok/sUD-Q2_K_XL
Qwen 3.6 27Boffload29tok/sQ8_0
Gemma 4 31Boffload24tok/sQ8_0
Qwen3 Coder Nextwon't run190tok/sQ4_K_M
Mistral Small 4 119Boffload195tok/sUD-Q2_K_XL
Qwen 3.6 35B-A3Boffload151tok/sQ8_0
Qwen 3.5 27Boffload29tok/sQ8_0
Gemma 4 26B-A4Boffload110tok/sQ8_0
GLM 4.5 Airwon't run69tok/sQ2_K
Devstral Small 2 24B35tok/sQ4_K_M32tok/sQ8_0
Qwen 3.5 35B-A3Boffload151tok/sQ8_0
GLM 4.7 Flashoffload87tok/sQ8_0
Qwen3 Next 80B-A3Bwon't run242tok/sQ4_K_M
Nemotron 3.5 Lightning 30B-A3Boffload146tok/sUD-Q6_K_XL
gpt-oss 20B127tok/sMXFP4190tok/sMXFP4
Qwen3 Coder 30B-A3Boffload125tok/sQ8_0
Kimi Linear 48B-A3Boffload194tok/sQ6_K
Qwen3 32Boffload23tok/sQ8_0
Gemma 4 12B42tok/sQ8_063tok/sQ8_0
Qwen 3.5 9B56tok/sQ8_085tok/sQ8_0
Mistral Small 3.2 24B35tok/sQ4_K_M32tok/sQ8_0
Gemma 3 27Boffload28tok/sQ8_0
DeepSeek R1 Distill Qwen 32Boffload23tok/sQ8_0
Llama 3.3 70Bwon't run18tok/sQ4_K_M
Qwen3 14B41tok/sQ6_K49tok/sQ8_0
Ministral 3 14B35tok/sQ8_053tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B56tok/sQ8_084tok/sQ8_0
Qwen3 8B56tok/sQ8_084tok/sQ8_0
Phi-4 14B41tok/sQ6_K48tok/sQ8_0
Qwen 3.5 4B116tok/sQ8_0174tok/sQ8_0
Ministral 3 8B55tok/sQ8_082tok/sQ8_0
Granite 4.2 8B52tok/sQ8_078tok/sQ8_0
Gemma 4 E4B66tok/sQ8_098tok/sQ8_0
LFM2.5 8B-A1B227tok/sQ8_0341tok/sQ8_0
Llama 3.1 8B72tok/sQ6_K109tok/sQ6_K
Qwen2.5 0.5B879tok/sQ8_01319tok/sQ8_0
Qwen3.5 0.8B596tok/sQ8_0895tok/sQ8_0
Qwen3.5 2B357tok/sQ5_K_M536tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B261tok/sQ8_0391tok/sQ8_0
MiniCPM5 2B183tok/sQ8_0275tok/sQ8_0
LFM2.5 2.6B164tok/sQ8_0247tok/sQ8_0
LFM2.5 VL 3B164tok/sQ8_0247tok/sQ8_0
Spark X2.5 4B163tok/smlx-4bit245tok/smlx-4bit
Kimi VL A3B Thinking 2506153tok/sQ4_K_M149tok/sQ8_0
granite vision 4.1 4b130tok/sQ8_0194tok/sQ8_0
Ministral 3 3B Instruct 2512123tok/sQ8_0184tok/sQ8_0
granite 4.2 3b122tok/sQ8_0183tok/sQ8_0
Kimi VL A3B120tok/smlx-6bit142tok/smlx-8bit
Mellum2.1 12B A2.5B Thinking118tok/sQ8_0177tok/sQ8_0
FrogNano 4B 2609112tok/sQ8_0169tok/sQ8_0
DeepSeek R1 Distill Qwen 7B65tok/sQ8_097tok/sQ8_0
GLM 4 9B 041465tok/smlx-5bit97tok/smlx-5bit
DeepSeek R1 Distill Llama 8B58tok/sQ8_087tok/sQ8_0
Ministral 3 8B Reasoning 251255tok/sQ8_082tok/sQ8_0
GLM 4.6V Flash54tok/sQ8_081tok/sQ8_0
GLM 4.1V 9B Thinking46tok/smlx-8bit69tok/smlx-8bit
DeepSeek R1 Distill Qwen 14B40tok/sQ6_K48tok/sQ8_0
Devstral Small 250735tok/sQ4_K_M32tok/sQ8_0
Magistral Small 250635tok/sQ4_K_M32tok/sQ8_0
Magistral Small 250735tok/sQ4_K_M32tok/sQ8_0
Magistral Small 250935tok/sQ4_K_M32tok/sQ8_0
Ministral 3 14B Reasoning 251235tok/sQ8_053tok/sQ8_0
LFM2.5 24B A2Boffload179tok/sQ8_0
Muse Glimmer 30Boffload26tok/sQ8_0
granite 4.2 30boffload25tok/sQ8_0
Qwen3.8 27B OBLITERATEDoffload39tok/smlx-4bit
DeepSeek R1 Distill Llama 70Bwon't run18tok/sQ4_K_M
MiniMax M2.7won't runoffload
Nemotron 3 Super 120B-A12Bwon't runoffload
gpt-oss 120Bwon't runoffload
Devstral 2 123B Instruct 2512won't runoffload
GLM 4.5Vwon't runoffload
GLM 4.6Vwon't runoffload
Kimi Dev 72Bwon't runoffload
Mistral Medium 3.5 128Bwon't runoffload
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon't runwon't run
Qwen 3.8 Flash Nextwon'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
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 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

Questions

Which is better for local AI, the NVIDIA GeForce RTX 5070 Ti or the NVIDIA RTX PRO 5000 Blackwell 48GB?
Choose the NVIDIA RTX PRO 5000 Blackwell 48GB to run bigger models. Choose the NVIDIA RTX PRO 5000 Blackwell 48GB for speed.
Which can run bigger models, the NVIDIA GeForce RTX 5070 Ti or the NVIDIA RTX PRO 5000 Blackwell 48GB?
At 8k context the NVIDIA RTX PRO 5000 Blackwell 48GB runs 68 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 43; only the NVIDIA RTX PRO 5000 Blackwell 48GB holds Qwen 3.8 27B.
Which is faster for local AI, the NVIDIA GeForce RTX 5070 Ti or the NVIDIA RTX PRO 5000 Blackwell 48GB?
On the models both run fully in memory, the NVIDIA RTX PRO 5000 Blackwell 48GB is about 1.5× as fast as the NVIDIA GeForce RTX 5070 Ti (estimated, median across models).

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