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Beelink GTR9 Pro Ryzen AI Max+ 395 128GB vs GMKtec EVO-X2 Ryzen AI Max+ 395 128GB

For running models locally, priced in Germany. At 128k context the first runs 67 models fully in memory, the second 67.

In short

Both have 128 GB of memory for models; the Beelink GTR9 Pro Ryzen AI Max+ 395 128GB has 256 GB/s of bandwidth and the GMKtec EVO-X2 Ryzen AI Max+ 395 128GB 256 GB/s. At 128k context both run the same 67 models we track fully in memory. On the models both run fully in memory, the Beelink GTR9 Pro Ryzen AI Max+ 395 128GB and the GMKtec EVO-X2 Ryzen AI Max+ 395 128GB are about as fast as each other (estimated).

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

Beelink GTR9 Pro Ryzen AI Max+ 395 128GB

Not priced here

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GMKtec EVO-X2 Ryzen AI Max+ 395 128GB

3.700 €

eBay

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Specifications

SpecBeelink GTR9 Pro Ryzen AI Max+ 395 128GBGMKtec EVO-X2 Ryzen AI Max+ 395 128GB
ChipRyzen AI Max+ 395 (Radeon 8060S)Ryzen AI Max+ 395 (Radeon 8060S)
Memory bus256-bit256-bit
Memory bandwidth256 GB/s256 GB/s
FP16 compute59.4 TFLOPS59.4 TFLOPS
SoftwareROCmROCm
Unified memory128 GB128 GB
GPU can use by default96 GB96 GB
GPU can use, tuned120 GB120 GB
Operating systemwindowswindows
ProcessorRyzen AI Max+ 395Ryzen AI Max+ 395
Storage2000 GB2000 GB

What each runs

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

ModelBeelink GTR9 Pro Ryzen AI Max+ 395 128GBGMKtec EVO-X2 Ryzen AI Max+ 395 128GB
Qwen 3.8 Flash Next3tok/sUD-Q3_K_XL3tok/sUD-Q3_K_XL
Qwen 3.8 27B4tok/sQ8_04tok/sQ8_0
Qwen 3.5 122B-A10B8tok/sQ5_K_M8tok/sQ5_K_M
Qwen 3.6 27B4tok/sQ8_04tok/sQ8_0
Qwen3 Coder Next11tok/sQ8_011tok/sQ8_0
gpt-oss 120B11tok/sMXFP411tok/sMXFP4
Nemotron 3 Super 120B-A12B8tok/sQ5_K_M8tok/sQ5_K_M
Gemma 4 31B3tok/sQ8_03tok/sQ8_0
Mistral Small 4 119B10tok/sQ6_K10tok/sQ6_K
Qwen 3.6 35B-A3B15tok/sQ8_015tok/sQ8_0
Qwen 3.5 27B4tok/sQ8_04tok/sQ8_0
Gemma 4 26B-A4B12tok/sQ8_012tok/sQ8_0
GLM 4.5 Air2tok/sQ4_K_M2tok/sQ4_K_M
Qwen 3.5 35B-A3B15tok/sQ8_015tok/sQ8_0
Qwen3 Next 80B-A3B13tok/sQ8_013tok/sQ8_0
GLM 4.7 Flash7tok/sQ8_07tok/sQ8_0
Devstral Small 2 24B3tok/sQ8_03tok/sQ8_0
Nemotron 3.5 Lightning 30B-A3B20tok/sUD-Q6_K_XL20tok/sUD-Q6_K_XL
Kimi Linear 48B-A3B20tok/sQ8_020tok/sQ8_0
gpt-oss 20B15tok/sMXFP415tok/sMXFP4
Qwen3 Coder 30B-A3B5tok/sQ8_05tok/sQ8_0
Qwen3 32B2tok/sQ8_02tok/sQ8_0
Gemma 4 12B9tok/sQ8_09tok/sQ8_0
Qwen 3.5 9B10tok/sQ8_010tok/sQ8_0
Gemma 3 27B4tok/sQ8_04tok/sQ8_0
Mistral Small 3.2 24B3tok/sQ8_03tok/sQ8_0
DeepSeek R1 Distill Qwen 32B2tok/sQ8_02tok/sQ8_0
Llama 3.3 70B2tok/sQ5_K_M2tok/sQ5_K_M
Ministral 3 14B4tok/sQ8_04tok/sQ8_0
Qwen3 14B4tok/sQ8_04tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B5tok/sQ8_05tok/sQ8_0
Qwen3 8B5tok/sQ8_05tok/sQ8_0
Phi-4 14B3tok/sQ8_03tok/sQ8_0
Qwen 3.5 4B16tok/sQ8_016tok/sQ8_0
Ministral 3 8B5tok/sQ8_05tok/sQ8_0
Granite 4.2 8B5tok/sQ8_05tok/sQ8_0
Gemma 4 E4B12tok/sQ8_012tok/sQ8_0
LFM2.5 8B-A1B11tok/sQ8_011tok/sQ8_0
Llama 3.1 8B6tok/sQ6_K6tok/sQ6_K
Qwen2.5 0.5B66tok/sQ8_066tok/sQ8_0
Qwen3.5 0.8B58tok/sQ8_058tok/sQ8_0
Qwen3.5 2B46tok/sQ5_K_M46tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B25tok/sQ8_025tok/sQ8_0
Mellum2.1 12B A2.5B Thinking18tok/sQ8_018tok/sQ8_0
MiniCPM5 2B17tok/sQ8_017tok/sQ8_0
LFM2.5 2.6B13tok/sQ8_013tok/sQ8_0
LFM2.5 VL 3B13tok/sQ8_013tok/sQ8_0
Kimi VL A3B Thinking 250612tok/sQ8_012tok/sQ8_0
Kimi VL A3B12tok/smlx-8bit12tok/smlx-8bit
GLM 4 9B 041410tok/smlx-5bit10tok/smlx-5bit
granite vision 4.1 4b10tok/sQ8_010tok/sQ8_0
granite 4.2 3b10tok/sQ8_010tok/sQ8_0
GLM 4.6V Flash9tok/sQ8_09tok/sQ8_0
DeepSeek R1 Distill Qwen 7B9tok/sQ8_09tok/sQ8_0
GLM 4.1V 9B Thinking8tok/smlx-8bit8tok/smlx-8bit
LFM2.5 24B A2B7tok/sQ8_07tok/sQ8_0
DeepSeek R1 Distill Llama 8B6tok/sQ8_06tok/sQ8_0
Ministral 3 8B Reasoning 25125tok/sQ8_05tok/sQ8_0
DeepSeek R1 Distill Qwen 14B3tok/sQ8_03tok/sQ8_0
Devstral Small 25073tok/sQ8_03tok/sQ8_0
Magistral Small 25063tok/sQ8_03tok/sQ8_0
Magistral Small 25073tok/sQ8_03tok/sQ8_0
Magistral Small 25093tok/sQ8_03tok/sQ8_0
GLM 4.5V3tok/sQ4_K_M3tok/sQ4_K_M
GLM 4.6V3tok/sQ4_K_M3tok/sQ4_K_M
granite 4.2 30b2tok/sQ8_02tok/sQ8_0
DeepSeek R1 Distill Llama 70B2tok/sQ5_K_M2tok/sQ5_K_M
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon'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 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 4.6won'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 can run bigger models, the Beelink GTR9 Pro Ryzen AI Max+ 395 128GB or the GMKtec EVO-X2 Ryzen AI Max+ 395 128GB?
At 128k context both run the same 67 models we track fully in memory.
Which is faster for local AI, the Beelink GTR9 Pro Ryzen AI Max+ 395 128GB or the GMKtec EVO-X2 Ryzen AI Max+ 395 128GB?
On the models both run fully in memory, the Beelink GTR9 Pro Ryzen AI Max+ 395 128GB and the GMKtec EVO-X2 Ryzen AI Max+ 395 128GB are about as fast as each other (estimated).

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