readygpu

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

For running models locally, priced in Germany. At 64k context the first runs 31 models fully in memory, the second 63.

In short

The NVIDIA RTX PRO 5000 Blackwell 48GB has more memory for models: 48 GB against 16 GB. At 64k context the NVIDIA RTX PRO 5000 Blackwell 48GB runs 63 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 31; 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

1.286 €

Amazon

Add to build
NVIDIA RTX PRO 5000 Blackwell 48GB

Not priced here

Add to build

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 27Boffload25tok/sQ8_0
Qwen 3.5 122B-A10Bwon't run98tok/sUD-Q2_K_XL
Qwen 3.6 27Boffload25tok/sQ8_0
Gemma 4 31Boffload22tok/sQ8_0
Mistral Small 4 119Boffload129tok/sUD-Q2_K_XL
Qwen 3.6 35B-A3Boffload112tok/sQ8_0
Qwen 3.5 27Boffload25tok/sQ8_0
Gemma 4 26B-A4Boffload88tok/sQ8_0
Qwen 3.5 35B-A3Boffload112tok/sQ8_0
GLM 4.7 Flashoffload57tok/sQ8_0
Devstral Small 2 24Boffload23tok/sQ8_0
Nemotron 3.5 Lightning 30B-A3Boffload132tok/sUD-Q6_K_XL
gpt-oss 20B83tok/sMXFP4124tok/sMXFP4
Kimi Linear 48B-A3Boffload164tok/sQ6_K
Qwen3 Coder 30B-A3Boffload52tok/sQ8_0
Qwen3 32Boffload19tok/sQ6_K
Gemma 4 12B40tok/sQ8_059tok/sQ8_0
Qwen 3.5 9B47tok/sQ8_071tok/sQ8_0
Gemma 3 27Boffload24tok/sQ8_0
Mistral Small 3.2 24Boffload23tok/sQ8_0
DeepSeek R1 Distill Qwen 32Boffload19tok/sQ6_K
Ministral 3 14Boffload33tok/sQ8_0
Qwen3 14Boffload32tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B38tok/sQ4_K_M45tok/sQ8_0
Qwen3 8B38tok/sQ4_K_M45tok/sQ8_0
Phi-4 14Boffload29tok/sQ8_0
Qwen 3.5 4B83tok/sQ8_0125tok/sQ8_0
Ministral 3 8B37tok/sQ5_K_M46tok/sQ8_0
Granite 4.2 8Boffload42tok/sQ8_0
Gemma 4 E4B55tok/sQ8_082tok/sQ8_0
LFM2.5 8B-A1B78tok/sQ8_0117tok/sQ8_0
Llama 3.1 8B37tok/sQ6_K55tok/sQ6_K
Qwen2.5 0.5B416tok/sQ8_0624tok/sQ8_0
Qwen3.5 0.8B340tok/sQ8_0509tok/sQ8_0
Qwen3.5 2B246tok/sQ5_K_M369tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B147tok/sQ8_0221tok/sQ8_0
MiniCPM5 2B101tok/sQ8_0152tok/sQ8_0
Spark X2.5 4B101tok/smlx-4bit151tok/smlx-4bit
Mellum2.1 12B A2.5B Thinking92tok/sQ8_0137tok/sQ8_0
Kimi VL A3B Thinking 250684tok/sQ4_K_M97tok/sQ8_0
FrogNano 4B 260982tok/sQ8_0122tok/sQ8_0
LFM2.5 2.6B81tok/sQ8_0121tok/sQ8_0
LFM2.5 VL 3B81tok/sQ8_0121tok/sQ8_0
Kimi VL A3B79tok/smlx-5bit94tok/smlx-8bit
granite vision 4.1 4b62tok/sQ8_093tok/sQ8_0
granite 4.2 3b60tok/sQ8_090tok/sQ8_0
Ministral 3 3B Instruct 251252tok/sQ8_078tok/sQ8_0
GLM 4 9B 041451tok/smlx-5bit76tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B47tok/sQ8_070tok/sQ8_0
GLM 4.6V Flash44tok/sQ8_066tok/sQ8_0
GLM 4.1V 9B Thinking38tok/smlx-8bit58tok/smlx-8bit
DeepSeek R1 Distill Llama 8B37tok/sQ6_K49tok/sQ8_0
Ministral 3 8B Reasoning 251237tok/sQ5_K_M46tok/sQ8_0
LFM2.5 24B A2Boffload67tok/sQ8_0
Muse Glimmer 30Boffload25tok/sQ8_0
Ministral 3 14B Reasoning 2512offload33tok/sQ8_0
DeepSeek R1 Distill Qwen 14Boffload29tok/sQ8_0
Devstral Small 2507offload23tok/sQ8_0
Magistral Small 2506offload23tok/sQ8_0
Magistral Small 2507offload23tok/sQ8_0
Magistral Small 2509offload23tok/sQ8_0
Qwen3.8 27B OBLITERATEDoffload33tok/smlx-4bit
granite 4.2 30boffload17tok/sQ8_0
Nemotron 3 Super 120B-A12Bwon't runoffload
Qwen3 Coder Nextwon't runoffload
gpt-oss 120Bwon't runoffload
GLM 4.5 Airwon't runoffload
Qwen3 Next 80B-A3Bwon't runoffload
Llama 3.3 70Bwon't runoffload
DeepSeek R1 Distill Llama 70Bwon't runoffload
GLM 4.5Vwon'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
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 4.6Vwon'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 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 64k context the NVIDIA RTX PRO 5000 Blackwell 48GB runs 63 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 31; 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).

More comparisons

More hardware for local AI