Lenovo releases 16-inch gaming laptop with Nvidia GeForce RTX 5070 12GB and 32 GB RAM

[Redaktion]

Lenovo has finally released one of its 16-inch gaming laptops with Nvidia's GeForce RTX 5070 12GB laptop GPU. Also packing a new Arrow Lake HX processor, the Legion Pro 5i 16IAX10 contains a 240 Hz display, 32 GB of RAM and undercuts existing GeForce RTX 5070 Ti options with the same amount of VRAM.

https://www.notebookcheck.net/Lenovo-releases-16-inch-gaming-laptop-with-Nvidia-GeForce-RTX-5070-12GB-and-32-GB-RAM.1401829.0.html

[local AI on this laptop]

If this did not have the 12 GB VRAM GPU, one could not run SOTA model huggingface.co/unsloth/Qwen3.6-35B-A3B-MTP-GGUF/blob/main/Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf with a good amount of context tokens:

.. 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 it does have the additional 12 GB of (fast) VRAM memory, this is how much context tokens one could fit on it[1]:
~231,000 = 16,384*(32GB RAM + 12GB VRAM - 6GB for the OS - 22.4GB for 35B-A3B-UD-Q4_K_XL - 1.5GB for the window manager)
(or ~198,000 context tokens when giving the OS 8 GB, instead of 6 GB)

Words = context tokens * 0.75, so about 173,000 words, which is pretty good.

There is also Qwen3.8-27B, which scores higher on AA[2], but it will run multiple times slower (use it if you care about quality and can wait much longer). Since it's also smaller than the 35B model, you will have more context tokens (in the formula use 17.9 GB (since the file Qwen3.6-27B-UD-Q4_K_XL.gguf is 17.9 GB), instead of 22.4 GB).

[1] reddit.com/r/Qwen_AI/comments/1vo8pjz/qwen3827b_kv_cache_works_out_to_64_kibtoken_so/
[2] artificialanalysis.ai/?models=qwen3-8-27b%2Cqwen3-8-27b-medium%2Cqwen3-8-27b-low%2Cqwen3-8-27b-non-reasoning%2Cqwen3-6-35b-a3b%2Cqwen3-6-35b-a3b-non-reasoning&intelligence=artificial-analysis-intelligence-index