ASUS Ascent GX10 128GB vs NVIDIA GeForce RTX 5090

For running models locally, priced in Canada. At 64k context the first runs 69 models fully in memory, the second 49.

In short

The ASUS Ascent GX10 128GB has more memory for models: 128 GB against 32 GB. At 64k context the ASUS Ascent GX10 128GB runs 69 of the models we track fully in memory and the NVIDIA GeForce RTX 5090 49; only the ASUS Ascent GX10 128GB holds DeepSeek V4 Flash. On the models both run fully in memory, the NVIDIA GeForce RTX 5090 is about 6.6× as fast as the ASUS Ascent GX10 128GB (estimated, median across models). In Canada the ASUS Ascent GX10 128GB costs $8,299 at Amazon and the NVIDIA GeForce RTX 5090 $10,300 at Amazon: the ASUS Ascent GX10 128GB is $2,001 cheaper.

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

Specifications

SpecASUS Ascent GX10 128GBNVIDIA GeForce RTX 5090
ChipGB10 Grace Blackwell–
Memory bus256-bit512-bit
Memory bandwidth273 GB/s1,792 GB/s
FP16 compute62 TFLOPS209 TFLOPS
SoftwareCUDACUDA
Unified memory128 GB–
GPU can use by default119 GB–
GPU can use, tuned122 GB–
Operating systemdgx-os–
Processor20-core Arm (GB10)–
Storage1000 GB–
GPU–GeForce RTX 5090
Memory–32 GB GDDR7
Board power–575 W
PCIe generation–Gen 5
PCIe lanes–x16

What each runs

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

ModelASUS Ascent GX10 128GBNVIDIA GeForce RTX 5090
DeepSeek V4 Flash8tok/sUD-Q2_K_XLwon't run
GLM 5.3 Flash11tok/sUD-Q2_K_XLwon't run
Qwen 3.8 Flash Next2tok/sQ4_K_Mwon't run
Qwen 3.8 27B5tok/sQ8_039tok/sQ6_K
MiniMax M2.75tok/sUD-Q3_K_Mwon't run
Qwen 3.5 122B-A10B10tok/sQ6_Koffload
Qwen 3.6 27B5tok/sQ8_041tok/sQ6_K
gpt-oss 120B18tok/sMXFP4won't run
Qwen3 Coder Next18tok/sQ8_0offload
Nemotron 3 Super 120B-A12B9tok/sUD-Q6_Koffload
Gemma 4 31B4tok/sQ8_035tok/sQ6_K
Mistral Small 4 119B14tok/sUD-Q6_Koffload
Qwen 3.6 35B-A3B23tok/sQ8_0167tok/sQ6_K
Qwen 3.5 27B5tok/sQ8_041tok/sQ6_K
Gemma 4 26B-A4B18tok/sQ8_0117tok/sQ8_0
GLM 4.5 Air4tok/sQ6_Koffload
Qwen 3.5 35B-A3B23tok/sQ8_0175tok/sQ6_K
Qwen3 Next 80B-A3B21tok/sQ8_0offload
GLM 4.7 Flash12tok/sQ8_087tok/sQ6_K
Devstral Small 2 24B5tok/sQ8_037tok/sQ6_K
Nemotron 3.5 Lightning 30B-A3B27tok/sUD-Q6_K_XLoffload
Kimi Linear 48B-A3B27tok/sQ8_0277tok/sQ4_K_M
gpt-oss 20B25tok/sMXFP4165tok/sMXFP4
Qwen3 Coder 30B-A3B11tok/sQ8_075tok/sQ6_K
Qwen3 32B3tok/sQ8_0offload
Gemma 4 12B12tok/sQ8_079tok/sQ8_0
Qwen 3.5 9B14tok/sQ8_095tok/sQ8_0
Gemma 3 27B5tok/sQ8_040tok/sQ6_K
Mistral Small 3.2 24B5tok/sQ8_037tok/sQ6_K
DeepSeek R1 Distill Qwen 32B3tok/sQ8_0offload
Llama 3.3 70B2tok/sQ8_0won't run
Ministral 3 14B7tok/sQ8_044tok/sQ8_0
Qwen3 14B6tok/sQ8_042tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B9tok/sQ8_061tok/sQ8_0
Qwen3 8B9tok/sQ8_061tok/sQ8_0
Phi-4 14B6tok/sQ8_038tok/sQ8_0
Qwen 3.5 4B25tok/sQ8_0166tok/sQ8_0
Ministral 3 8B9tok/sQ8_061tok/sQ8_0
Granite 4.2 8B8tok/sQ8_055tok/sQ8_0
Gemma 4 E4B17tok/sQ8_0110tok/sQ8_0
LFM2.5 8B-A1B24tok/sQ8_0156tok/sQ8_0
Llama 3.1 8B11tok/sQ6_K73tok/sQ6_K
Qwen2.5 0.5B127tok/sQ8_0831tok/sQ8_0
Qwen3.5 0.8B104tok/sQ8_0679tok/sQ8_0
Qwen3.5 2B75tok/sQ5_K_M492tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B45tok/sQ8_0294tok/sQ8_0
MiniCPM5 2B31tok/sQ8_0202tok/sQ8_0
Mellum2.1 12B A2.5B Thinking28tok/sQ8_0183tok/sQ8_0
LFM2.5 2.6B25tok/sQ8_0161tok/sQ8_0
LFM2.5 VL 3B25tok/sQ8_0161tok/sQ8_0
Kimi VL A3B19tok/smlx-8bit126tok/smlx-8bit
granite vision 4.1 4b19tok/sQ8_0124tok/sQ8_0
granite 4.2 3b18tok/sQ8_0120tok/sQ8_0
DeepSeek R1 Distill Qwen 7B14tok/sQ8_094tok/sQ8_0
LFM2.5 24B A2B14tok/sQ8_089tok/sQ8_0
GLM 4.6V Flash13tok/sQ8_088tok/sQ8_0
GLM 4.1V 9B Thinking12tok/smlx-8bit77tok/smlx-8bit
DeepSeek R1 Distill Llama 8B10tok/sQ8_065tok/sQ8_0
Ministral 3 8B Reasoning 25129tok/sQ8_061tok/sQ8_0
DeepSeek R1 Distill Qwen 14B6tok/sQ8_039tok/sQ8_0
Devstral Small 25075tok/sQ8_040tok/sQ5_K_M
Magistral Small 25065tok/sQ8_037tok/sQ6_K
Magistral Small 25075tok/sQ8_040tok/sQ5_K_M
Magistral Small 25095tok/sQ8_040tok/sQ5_K_M
GLM 4.5V4tok/sQ8_0won't run
GLM 4.6V4tok/sQ8_0won't run
granite 4.2 30b4tok/sQ8_0offload
DeepSeek R1 Distill Llama 70B2tok/sQ8_0won't run
Mistral Medium 3.5 128B1tok/sQ6_Kwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won'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 4.7won'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

Questions

Which is better for local AI, the ASUS Ascent GX10 128GB or the NVIDIA GeForce RTX 5090?
Choose the ASUS Ascent GX10 128GB to run bigger models. Choose the NVIDIA GeForce RTX 5090 for speed. Choose the ASUS Ascent GX10 128GB to spend less.
Which can run bigger models, the ASUS Ascent GX10 128GB or the NVIDIA GeForce RTX 5090?
At 64k context the ASUS Ascent GX10 128GB runs 69 of the models we track fully in memory and the NVIDIA GeForce RTX 5090 49; only the ASUS Ascent GX10 128GB holds DeepSeek V4 Flash.
Which is faster for local AI, the ASUS Ascent GX10 128GB or the NVIDIA GeForce RTX 5090?
On the models both run fully in memory, the NVIDIA GeForce RTX 5090 is about 6.6× as fast as the ASUS Ascent GX10 128GB (estimated, median across models).
What is the price difference between the ASUS Ascent GX10 128GB and the NVIDIA GeForce RTX 5090?
In Canada the ASUS Ascent GX10 128GB costs $8,299 at Amazon and the NVIDIA GeForce RTX 5090 $10,300 at Amazon: the ASUS Ascent GX10 128GB is $2,001 cheaper.

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