2500 bucks for only 32 GB soldered RAM and 8 GB VRAM.
If gaming is the primary target -- 8 GB VRAM:
youtube.com/watch?v=ric7yb1VaoA: "Gaming Laptops are in Trouble - VRAM Testing w/ ‪@Hardwareunboxed‬".
12 GB VRAM on the same 128-bit bus are around the corner (using 3 GB instead the current 2 GB dense GDDR7 chips) according to: notebookcheck.net/Lenovo-confirms-RTX-5070-12GB-gaming-laptops-launching-soon-with-Intel-Core-Ultra-7-251HX-models-also-joining.1255561.0.html
If running AI / LLMs locally is the primary target:
If this hadn't the 8 GB VRAM GPU, then the 32 GB RAM would not be enough for the new SOTA LLM, Qwen3.6-35B-A3B-UD-Q4_K_M, in agentic workflows:
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.
But since this laptop has additional 8 GB VRAM, parts of the LLM can be offloaded to it. This increases the context from 32k to roughly 148k, according to huggingface.co/spaces/oobabooga/accurate-gguf-vram-calculator (paste this into its "GGUF Model URL" field: huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF/blob/main/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf), which is pretty good.
For the same money you could build a much more capable desktop PC and it would be repairable, upgradable and run cooler and probably also quieter.
Arbitrary memory size times memory speed (aka bandwidth) score:
(RAM: 136.5 GB/s = 128-bit * 8533 MT/s / 1000 / 8.
VRAM (5060 Laptop): 384 GB/s.)
7440 (= 32 GB RAM * 136.5 GB/s + 8 GB VRAM * 384 GB/s)
For comparison, a 128 GB RAM Strix Halo scores:
(RAM: 256 GB/s = 256-bit * 8000 MT/s / 1000 / 8.)
32768 (= 128 GB RAM * 256 GB/s)
The only issue with Strix Halo (Radeon 8060S) is that its prompt processing speed is that of a 4060 Laptop, so just a bit slower than what is in this Legion 7a 16 G11 laptop.
Running/inferencing AI / LLMs requires these things:
- Memory size to fit a decently capable LLM, including memory left for context and memory speed (aka memory bandwidth).
- Prompt processing: The larger the input, the faster GPU you'd need, especially for agentic workflows, if you want things to finish in reasonable time.
- Token generation: The speed of the output generation depends on memory speed (aka memory bandwidth).
Wow, those DPC latencies will sure make using this laptop enjoyable... Unbelievable incompetence, just straight up embarrassing in this day and age.
Quote from: it says WAIT on April 25, 2026, 12:34:33The only issue with Strix Halo (Radeon 8060S) is that its prompt processing speed is that of a 4060 Laptop
I'd like to know how the M5 Air, Panther Lake and Snapdragon X2 Elite compare.