readygpu

Intel Arc Pro B70 vs NVIDIA GeForce RTX 5070 Ti

For running models locally, priced in Germany. At 128k context the first runs 50 models fully in memory, the second 22.

In short

The Intel Arc Pro B70 has more memory for models: 32 GB against 16 GB. At 128k context the Intel Arc Pro B70 runs 50 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 22; only the Intel Arc Pro B70 holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 5070 Ti is about 1.8× as fast as the Intel Arc Pro B70 (estimated, median across models).

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

Intel Arc Pro B70

Not priced here

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NVIDIA GeForce RTX 5070 Ti

1.286 €

Amazon

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Specifications

SpecIntel Arc Pro B70NVIDIA GeForce RTX 5070 Ti
GPUArc Pro B70GeForce RTX 5070 Ti
Memory32 GB GDDR616 GB GDDR7
Memory bus256-bit256-bit
Memory bandwidth608 GB/s896 GB/s
FP16 compute45.8 TFLOPS88 TFLOPS
SoftwareSYCL / oneAPICUDA
Board power230 W300 W
PCIe generationGen 5Gen 5
PCIe lanesx16x16

What each runs

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

ModelIntel Arc Pro B70NVIDIA GeForce RTX 5070 Ti
Qwen 3.8 27B10tok/sUD-Q6_Koffload
Qwen 3.6 27B10tok/sQ6_Koffload
Gemma 4 31B10tok/sQ4_K_Moffload
Qwen 3.6 35B-A3B34tok/sUD-Q5_K_Moffload
Qwen 3.5 27B10tok/sQ6_Koffload
Gemma 4 26B-A4B24tok/sQ8_0offload
Qwen 3.5 35B-A3B32tok/sQ6_Koffload
GLM 4.7 Flash15tok/sQ6_Koffload
Nemotron 3.5 Lightning 30B-A3B45tok/sUD-Q5_K_Moffload
Kimi Linear 48B-A3B57tok/sQ4_K_Moffload
gpt-oss 20B30tok/sMXFP460tok/sQ4_K_M
Qwen3 Coder 30B-A3B11tok/sQ4_K_Moffload
Gemma 4 12B20tok/sQ8_045tok/sQ6_K
Qwen 3.5 9B22tok/sQ8_040tok/sQ8_0
Gemma 3 27B10tok/sQ5_K_Moffload
Qwen3 14B10tok/sQ4_K_Moffload
Ministral 3 14B10tok/sQ5_K_Moffload
DeepSeek R1 0528 Qwen3 8B11tok/sQ8_0offload
Qwen3 8B11tok/sQ8_0offload
Qwen 3.5 4B34tok/sQ8_063tok/sQ8_0
Ministral 3 8B11tok/sQ8_0offload
Granite 4.2 8B10tok/sQ8_0offload
Gemma 4 E4B25tok/sQ8_046tok/sQ8_0
LFM2.5 8B-A1B22tok/sQ8_046tok/sUD-Q6_K
Llama 3.1 8B13tok/sQ6_Koffload
Qwen2.5 0.5B142tok/sQ8_0259tok/sQ8_0
Qwen3.5 0.8B125tok/sQ8_0228tok/sQ8_0
Qwen3.5 2B99tok/sQ5_K_M181tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B54tok/sQ8_098tok/sQ8_0
Spark X2.5 4B38tok/smlx-4bit70tok/smlx-4bit
MiniCPM5 2B37tok/sQ8_067tok/sQ8_0
Mellum2.1 12B A2.5B Thinking37tok/sQ8_073tok/sQ8_0
FrogNano 4B 260934tok/sQ8_062tok/sQ8_0
LFM2.5 2.6B28tok/sQ8_051tok/sQ8_0
LFM2.5 VL 3B28tok/sQ8_051tok/sQ8_0
Kimi VL A3B Thinking 250623tok/sQ8_056tok/sQ4_K_M
Kimi VL A3B23tok/smlx-8bitoffload
GLM 4 9B 041422tok/smlx-5bit41tok/smlx-5bit
granite vision 4.1 4b21tok/sQ8_039tok/sQ8_0
granite 4.2 3b21tok/sQ8_038tok/sQ8_0
GLM 4.6V Flash20tok/sQ8_048tok/sQ4_K_M
DeepSeek R1 Distill Qwen 7B20tok/sQ8_040tok/sQ6_K
GLM 4.1V 9B Thinking18tok/smlx-8bitoffload
Ministral 3 3B Instruct 251217tok/sQ8_0offload
LFM2.5 24B A2B14tok/sQ5_K_Moffload
Muse Glimmer 30B12tok/sQ6_Koffload
DeepSeek R1 Distill Llama 8B12tok/sQ8_0offload
Ministral 3 8B Reasoning 251211tok/sQ8_0offload
Qwen3.8 27B OBLITERATED10tok/smlx-4bitoffload
Ministral 3 14B Reasoning 251210tok/sQ5_K_Moffload
Qwen 3.5 122B-A10Boffloadwon't run
Qwen3 Coder Nextoffloadwon't run
Nemotron 3 Super 120B-A12Boffloadwon't run
Mistral Small 4 119Boffloadwon't run
Qwen3 Next 80B-A3Boffloadwon't run
Devstral Small 2 24Boffloadoffload
Qwen3 32Boffloadwon't run
Mistral Small 3.2 24Boffloadoffload
DeepSeek R1 Distill Qwen 32Boffloadwon't run
Phi-4 14Boffloadoffload
DeepSeek R1 Distill Qwen 14Boffloadoffload
Devstral Small 2507offloadoffload
Magistral Small 2506offloadoffload
Magistral Small 2507offloadoffload
Magistral Small 2509offloadoffload
granite 4.2 30boffloadwon't run
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
gpt-oss 120Bwon't runwon't run
GLM 4.5 Airwon't runwon't run
Llama 3.3 70Bwon't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek R1 Distill Llama 70Bwon'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 4.5Vwon'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 Intel Arc Pro B70 or the NVIDIA GeForce RTX 5070 Ti?
Choose the Intel Arc Pro B70 to run bigger models. Choose the NVIDIA GeForce RTX 5070 Ti for speed.
Which can run bigger models, the Intel Arc Pro B70 or the NVIDIA GeForce RTX 5070 Ti?
At 128k context the Intel Arc Pro B70 runs 50 of the models we track fully in memory and the NVIDIA GeForce RTX 5070 Ti 22; only the Intel Arc Pro B70 holds Qwen 3.8 27B.
Which is faster for local AI, the Intel Arc Pro B70 or the NVIDIA GeForce RTX 5070 Ti?
On the models both run fully in memory, the NVIDIA GeForce RTX 5070 Ti is about 1.8× as fast as the Intel Arc Pro B70 (estimated, median across models).

More comparisons

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