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AMD Radeon AI PRO R9700 vs NVIDIA GeForce RTX 5080

For running models locally, priced in Germany. At 128k context the first runs 41 models fully in memory, the second 18.

In short

The AMD Radeon AI PRO R9700 has more memory for models: 32 GB against 16 GB. At 128k context the AMD Radeon AI PRO R9700 runs 41 of the models we track fully in memory and the NVIDIA GeForce RTX 5080 18; only the AMD Radeon AI PRO R9700 holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 5080 is about 1.7× as fast as the AMD Radeon AI PRO R9700 (estimated, median across models). In Germany the AMD Radeon AI PRO R9700 costs 1.867 € at Amazon and the NVIDIA GeForce RTX 5080 1.599 € at Amazon: the NVIDIA GeForce RTX 5080 is 268 € cheaper.

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

AMD Radeon AI PRO R9700

1.867 €

Amazon

Add to build
NVIDIA GeForce RTX 5080

1.599 €

Amazon

Add to build

Specifications

SpecAMD Radeon AI PRO R9700NVIDIA GeForce RTX 5080
GPURadeon AI PRO R9700GeForce RTX 5080
Memory32 GB GDDR616 GB GDDR7
Memory bus256-bit256-bit
Memory bandwidth640 GB/s960 GB/s
FP16 compute191 TFLOPS113 TFLOPS
SoftwareROCmCUDA
Board power300 W360 W
PCIe generationGen 5Gen 5
PCIe lanesx16x16

What each runs

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

ModelAMD Radeon AI PRO R9700NVIDIA GeForce RTX 5080
Qwen 3.8 27B12tok/sUD-Q6_Koffload
Qwen 3.6 27B11tok/sQ6_Koffload
Gemma 4 31B12tok/sQ4_K_Moffload
Qwen 3.6 35B-A3B43tok/sUD-Q5_K_Moffload
Qwen 3.5 27B11tok/sQ6_Koffload
Gemma 4 26B-A4B30tok/sQ8_0offload
Qwen 3.5 35B-A3B41tok/sQ6_Koffload
GLM 4.7 Flash19tok/sQ6_Koffload
Kimi Linear 48B-A3B72tok/sQ4_K_Moffload
gpt-oss 20B37tok/sMXFP464tok/sQ4_K_M
Qwen3 Coder 30B-A3B14tok/sQ4_K_Moffload
Gemma 4 12B23tok/sQ8_049tok/sQ6_K
Qwen 3.5 9B25tok/sQ8_043tok/sQ8_0
Gemma 3 27B12tok/sQ5_K_Moffload
Qwen3 14B12tok/sQ4_K_Moffload
Ministral 3 14B11tok/sQ5_K_Moffload
DeepSeek R1 0528 Qwen3 8B13tok/sQ8_0offload
Qwen3 8B13tok/sQ8_0offload
Qwen 3.5 4B40tok/sQ8_067tok/sQ8_0
Ministral 3 8B13tok/sQ8_0offload
Granite 4.2 8B11tok/sQ8_0offload
Gemma 4 E4B29tok/sQ8_050tok/sQ8_0
LFM2.5 8B-A1B28tok/sQ8_049tok/sUD-Q6_K
Llama 3.1 8B15tok/sQ6_Koffload
Qwen2.5 0.5B164tok/sQ8_0278tok/sQ8_0
Qwen3.5 0.8B144tok/sQ8_0244tok/sQ8_0
Qwen3.5 2B115tok/sQ5_K_M194tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B62tok/sQ8_0105tok/sQ8_0
Mellum2.1 12B A2.5B Thinking46tok/sQ8_078tok/sQ8_0
MiniCPM5 2B42tok/sQ8_072tok/sQ8_0
LFM2.5 2.6B32tok/sQ8_055tok/sQ8_0
LFM2.5 VL 3B32tok/sQ8_055tok/sQ8_0
Kimi VL A3B29tok/smlx-8bitoffload
granite vision 4.1 4b25tok/sQ8_042tok/sQ8_0
granite 4.2 3b24tok/sQ8_041tok/sQ8_0
GLM 4.6V Flash23tok/sQ8_052tok/sQ4_K_M
DeepSeek R1 Distill Qwen 7B23tok/sQ8_043tok/sQ6_K
GLM 4.1V 9B Thinking21tok/smlx-8bitoffload
LFM2.5 24B A2B17tok/sQ5_K_Moffload
DeepSeek R1 Distill Llama 8B14tok/sQ8_0offload
Ministral 3 8B Reasoning 251213tok/sQ8_0offload
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
Nemotron 3.5 Lightning 30B-A3Boffloadoffload
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 V3 0324won't runwon't run
DeepSeek V3.1won'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 4.6Vwon'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 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 AMD Radeon AI PRO R9700 or the NVIDIA GeForce RTX 5080?
Choose the AMD Radeon AI PRO R9700 to run bigger models. Choose the NVIDIA GeForce RTX 5080 for speed. Choose the NVIDIA GeForce RTX 5080 to spend less.
Which can run bigger models, the AMD Radeon AI PRO R9700 or the NVIDIA GeForce RTX 5080?
At 128k context the AMD Radeon AI PRO R9700 runs 41 of the models we track fully in memory and the NVIDIA GeForce RTX 5080 18; only the AMD Radeon AI PRO R9700 holds Qwen 3.8 27B.
Which is faster for local AI, the AMD Radeon AI PRO R9700 or the NVIDIA GeForce RTX 5080?
On the models both run fully in memory, the NVIDIA GeForce RTX 5080 is about 1.7× as fast as the AMD Radeon AI PRO R9700 (estimated, median across models).
What is the price difference between the AMD Radeon AI PRO R9700 and the NVIDIA GeForce RTX 5080?
In Germany the AMD Radeon AI PRO R9700 costs 1.867 € at Amazon and the NVIDIA GeForce RTX 5080 1.599 € at Amazon: the NVIDIA GeForce RTX 5080 is 268 € cheaper.

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