It would have been nice if they released a, say, 24 GB RAM "OnePlus 16 AI" config.

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))