Quote from: AI+ on May 08, 2026, 09:42:00This laptop doesn't really deserve any AI in its product name:
AI, both for traning and for the endconsumer/inferencing requires these 3 things:
1. Memory size, to fit a decently capable LLM.
32 GB RAM may not enough for the new SOTA LLM, especially in agentic workflows: Qwen3.6-35B-A3B-UD-Q4_K_M:
Quote from: reddit.com/r/LocalLLaMA/comments/1sq94qx/is_anyone_getting_real_coding_work_done_with.. I've come to the conclusion that (1) 32768 is the biggest context I can get away with in an adequately smart model, and (2) it just ain't enough.
2. Memory speed, also known as bandwidth, relevant for token generation (output) speed.
The memory speed is 109298 MB/s, this is in line with any dual-channel/128-bit/2*64-bit, PC/laptop, running at 8533 MT/s (like 99% of all PCs/laptops are dual-channel/128-bit/2*64-bit). So, this is nothing special, except only new devices are going to run at 8000 MT/s or above, like e.g. a Strix Halo' 256-bit at 8000 MT/s, which is 2x the bandwidth of what this offers. 109298 MB/s is not bad, but it's only 32 GB RAM and no GPU, so no additional much faster VRAM to offload to.
3. GPU compute, relevant for prompt processing (input) speed.
Prompt processing: The larger the input, the faster the GPU you'd need, especially for agentic workflows. The prompt processing speed is based on GPU' FPS number in games/3D benchmarks. Here, the iGPU scores 6178 Points in 2560x1440 Time Spy Graphics. For comparison, a 5070 desktop: 3dmark.com/search: "Average score: 20330".
(The number of CPU threads doesn't matter for running AI (aka inferencing) (4 threads pretty much tops-out a dual-channel PC))
So, in short for those who don't know: You can build a desktop PC for a fraction of the price and it will be upgradable, repairable, have a much faster GPU, run quieter, cooler and therefore probably also last longer.
Just for comparison -- Total memory capacity times speed score calculation:
This: 4369 = 32 GB RAM * 136.5 GB/s [=128-bit * 8533MT/s / 1000 / 8].
Strix Halo: 32768 = 128 GB * 256 GB/s [=256-bit * 8000MT/s / 1000 / 8].
3dmark.com/search:
Arc B390 (tho it scores a lower 6178 score in this laptop): "Average score: 7251".
Strix Halo' Radeon 8060S iGPU: "Average score: 10014".
QuoteCPU temperature warmer than average
When I read this I though it is going to be an INTEL CPU and scrolling down, it surely is xd.
Basically same with this notebook:
2560x1440 Time Spy Graphics (relevant for prompt processing): 6627 Points.
AIDA64 Memory Read (relevant for token generation): 97755 MB/s.
For the mentioned SOTA LLM: Has a notebook a total memory size of ~48 GB RAM+VRAM (32 GB RAM + 8 GB VRAM may also be enough), then there would be enough memory/context for agentic workflows. The 32k context (according to that reddit quote) that 32 GB RAM [and no dGPU] allows, may also not be enough for non-agentic workflows. This 32 GB RAM issue weights by far the most, as running something slower (no dGPU's much faster VRAM and much faster prompt processing) is better than not being able to fit and run at all.
A normal gaming laptop with upgradable RAM to 48 or 64 GB RAM (even if it's only 5600 MT/s and not 8000 MT/s) + its much faster dGPU for AI prompt processing actually deserves an "AI" in its product name compared to this laptop.
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