QuoteThe standard retail model comes with 64 GB of memory, while Thunderobot says the M7000 can support up to 128 GB.
Good, because I was gonna write that this 4060 Laptop performing laptop would be neither here, nor there, if it only supported up to 64 GB RAM/unified memory, instead of the full 128 GB RAM, that would allow it to run SOTA AI LLM model Qwen3.8-Flash-Next (e.g. huggingface.co/unsloth/Qwen3.8-Flash-Next-GGUF/tree/main/UD-Q4_K_XL): While the quant is 111 GB, the n-gram embeddings are 30 GB and are streamed from the SSD with almost no performance impact. So it becomes 111 GB - 30 GB = 81 GB.
On Windows: 128 GB RAM - 32 GB RAM = 96 GB RAM freely available for any AI LLM model and 81 GB fit comfortably into 96 GB RAM + decent amount of context.
On Linux (search for 'strix halo linux gtt'): 128 GB RAM - 8 GB RAM = 120 GB RAM freely available for any AI LLM model and 81 GB fit very comfortably into 96 GB RAM + big amount of context.
For 3000 bucks you can build a desktop PC that will be faster for AI:
- this (64 GB RAM/unified memory at 256 GB/s) / any 64 GB Strix Halo: AI score: 16384 = 64 GB * 256 GB/s.
vs
- desktop PC build using 64 GB RAM + two 5060 Ti 16GB: AI score: 34406 = (64 GB * 89.6 GB/s (DDR5 5600 MT/s)) + (2*16 GB*2*448 GB/s (in tensor split mode the memory bandwidth doubles))