HP releases new 16-inch laptop with Intel Wildcat Lake and up to 24 GB RAM

[Redaktion]

HP has brought Intel's Wildcat Lake platform to its business-focused HP 200 series. Available as the HP 200 G2Ri 16, the 16-inch laptop can currently be configured with up to 24 GB RAM and the Core 7 350.

https://www.notebookcheck.net/HP-releases-new-16-inch-laptop-with-Intel-Wildcat-Lake-and-up-to-24-GB-RAM.1422252.0.html

[AI on 24 GB RAM]

one can configure up to 24 GB of RAM

With 24 GB of unified memory/RAM, your best bet would be to try to run a minimum useful Q4_K_M quant of, in this case, a approx. 24B AI LLM model[1].

2.5 GB for remaining context tokens = 24 GB - 7 GB for the OS[2] - 14.5 GB for the quant[3].
2.5 GB for context is not a lot.

huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF Q4_K_M is 16.9 GB, so unfortunately it won't fit.

[1] More small models to choose from: artificialanalysis.ai/models/open-source/small (maybe LFM2.5-24B-A2B will also be evaluated there soon).
[2] techpowerup.com/353395/windows-11-26h2-update-lowers-ram-consumption
[3] e.g. huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Q4_K_M quant.
These ~30B parameters models, that you can run locally on 32 GB unified memory/RAM + 8 GB VRAM GPU, are no joke:

Once again anthropic doing free marketing for open weight models

Models of 30B parameters and under can already complete many of the individual steps for replication today, though they make mistakes when composing them end to end. In our simplified evaluations, GLM-5.2 and stronger models are capable of end to end replication. If small models improve at their historical rate, they'll match this capability level by the end of this year. Small weight-based replicators may be possible soon after.

And the top rated comment from that reddit post is:

they talking about our goat 27b

PS: Qwen4-27B has been announced (reddit.com/r/LocalLLaMA/comments/1wmxfjs/qwen_4_announced_at_apsara_conference) and is rumored to be released by the end of october, but 24 GB of total memory wont be able to fit a minimally required, good, Q4_K_M quant (same calculation as above, but instead of 14.5 GB, use 16.5 GB (e.g. huggingface.co/unsloth/Qwen3.8-27B-GGUF).