readygpu

Intel Arc A770 16GB vs NVIDIA Tesla P40

For running models locally, priced in Germany. At 32k context the first runs 32 models fully in memory, the second 53.

In short

The NVIDIA Tesla P40 has more memory for models: 24 GB against 16 GB. At 32k context the NVIDIA Tesla P40 runs 53 of the models we track fully in memory and the Intel Arc A770 16GB 32; only the NVIDIA Tesla P40 holds Qwen 3.8 27B. On the models both run fully in memory, the Intel Arc A770 16GB is about 1.3× as fast as the NVIDIA Tesla P40 (estimated, median across models).

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

Intel Arc A770 16GB

390 €

Amazon

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NVIDIA Tesla P40

Not priced here

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Specifications

SpecIntel Arc A770 16GBNVIDIA Tesla P40
GPUArc A770 16GBTesla P40
Memory16 GB GDDR624 GB GDDR5
Memory bus256-bit384-bit
Memory bandwidth560 GB/s346 GB/s
FP16 compute131 TFLOPS11.8 TFLOPS
SoftwareSYCL / oneAPICUDA
Board power225 W250 W
PCIe generationGen 4Gen 3
PCIe lanesx16x16

What each runs

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

ModelIntel Arc A770 16GBNVIDIA Tesla P40
Qwen 3.8 27Boffload9tok/sQ5_K_M
Qwen 3.6 27Boffload10tok/sQ5_K_M
Gemma 4 31Boffload10tok/sQ4_K_M
Qwen 3.6 35B-A3Boffload50tok/sQ4_K_M
Qwen 3.5 27Boffload10tok/sQ5_K_M
Gemma 4 26B-A4Boffload29tok/sUD-Q6_K
Qwen 3.5 35B-A3Boffload50tok/sQ4_K_M
GLM 4.7 Flashoffload24tok/sQ5_K_M
Devstral Small 2 24Boffload10tok/sQ5_K_M
Nemotron 3.5 Lightning 30B-A3Boffload52tok/sMXFP4
gpt-oss 20B48tok/sMXFP440tok/sMXFP4
Qwen3 Coder 30B-A3Boffload26tok/sQ4_K_M
Gemma 4 12B21tok/sQ8_016tok/sQ8_0
Qwen 3.5 9B26tok/sQ8_020tok/sQ8_0
Gemma 3 27Boffload10tok/sQ5_K_M
Mistral Small 3.2 24Boffload10tok/sQ5_K_M
Qwen3 14B20tok/sQ4_K_M10tok/sQ8_0
Ministral 3 14B19tok/sQ5_K_M11tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B21tok/sQ8_016tok/sQ8_0
Qwen3 8B21tok/sQ8_016tok/sQ8_0
Phi-4 14Boffload10tok/sQ8_0
Qwen 3.5 4B50tok/sQ8_038tok/sQ8_0
Ministral 3 8B21tok/sQ8_016tok/sQ8_0
Granite 4.2 8B19tok/sQ8_015tok/sQ8_0
Gemma 4 E4B31tok/sQ8_023tok/sQ8_0
LFM2.5 8B-A1B58tok/sQ8_048tok/sQ8_0
Llama 3.1 8B26tok/sQ6_K20tok/sQ6_K
Qwen2.5 0.5B300tok/sQ8_0230tok/sQ8_0
Qwen3.5 0.8B227tok/sQ8_0174tok/sQ8_0
Qwen3.5 2B151tok/sQ5_K_M116tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B99tok/sQ8_076tok/sQ8_0
MiniCPM5 2B69tok/sQ8_053tok/sQ8_0
Spark X2.5 4B65tok/smlx-4bit50tok/smlx-4bit
LFM2.5 2.6B57tok/sQ8_044tok/sQ8_0
LFM2.5 VL 3B57tok/sQ8_044tok/sQ8_0
Kimi VL A3B Thinking 250652tok/sQ4_K_M31tok/sQ8_0
Mellum2.1 12B A2.5B Thinking49tok/sQ8_041tok/sQ8_0
granite vision 4.1 4b44tok/sQ8_034tok/sQ8_0
Kimi VL A3B43tok/smlx-6bit30tok/smlx-8bit
granite 4.2 3b43tok/sQ8_033tok/sQ8_0
GLM 4 9B 041429tok/smlx-5bit22tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B28tok/sQ8_022tok/sQ8_0
GLM 4.6V Flash25tok/sQ8_019tok/sQ8_0
DeepSeek R1 Distill Llama 8B22tok/sQ8_017tok/sQ8_0
GLM 4.1V 9B Thinking21tok/smlx-8bit16tok/smlx-8bit
Ministral 3 8B Reasoning 251221tok/sQ8_016tok/sQ8_0
LFM2.5 24B A2Boffload29tok/sQ6_K
DeepSeek R1 Distill Qwen 14Boffload10tok/sQ8_0
Devstral Small 2507offload10tok/sQ5_K_M
Magistral Small 2506offload10tok/sQ5_K_M
Magistral Small 2507offload10tok/sQ5_K_M
Magistral Small 2509offload10tok/sQ5_K_M
Qwen3.8 27B OBLITERATEDoffload9tok/smlx-4bit
Qwen 3.5 122B-A10Boffloadoffload
Qwen3 Coder Nextwon't runoffload
Mistral Small 4 119Boffloadoffload
GLM 4.5 Airwon't runoffload
Qwen3 Next 80B-A3Bwon't runoffload
Kimi Linear 48B-A3Boffloadoffload
Qwen3 32Boffloadoffload
DeepSeek R1 Distill Qwen 32Boffloadoffload
granite 4.2 30boffloadoffload
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
Nemotron 3 Super 120B-A12Bwon't runwon't run
gpt-oss 120Bwon'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 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 4.5Vwon'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 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 A770 16GB or the NVIDIA Tesla P40?
Choose the NVIDIA Tesla P40 to run bigger models. Choose the Intel Arc A770 16GB for speed.
Which can run bigger models, the Intel Arc A770 16GB or the NVIDIA Tesla P40?
At 32k context the NVIDIA Tesla P40 runs 53 of the models we track fully in memory and the Intel Arc A770 16GB 32; only the NVIDIA Tesla P40 holds Qwen 3.8 27B.
Which is faster for local AI, the Intel Arc A770 16GB or the NVIDIA Tesla P40?
On the models both run fully in memory, the Intel Arc A770 16GB is about 1.3× as fast as the NVIDIA Tesla P40 (estimated, median across models).

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