YOU ARE VIEWING ONE ITEM FROM THE AICRIER FEED

Reddit asks which laptop runs Qwen3.5-35B-A3B locally

AICrier tracks AI developer news across Product Hunt, GitHub, Hacker News, YouTube, X, arXiv, and more. This page keeps the article you opened front and center while giving you a path into the live feed.

// WHAT AICRIER DOES

7+

TRACKED FEEDS

24/7

SCRAPED FEED

Short summaries, external links, screenshots, relevance scoring, tags, and featured picks for AI builders.

Reddit asks which laptop runs Qwen3.5-35B-A3B locally
OPEN LINK ↗
// 74d agoTUTORIAL

Reddit asks which laptop runs Qwen3.5-35B-A3B locally

A developer on r/LocalLLaMA asks which budget laptop (~$1000) can run Qwen3.5-35B-A3B locally for private coding. The post compares several configurations — from RTX 4060 with 64GB RAM to RTX 5080 with 64GB — after finding that an MSI Vector GP68 with RTX 4080 12GB VRAM and 64GB RAM achieves 11 t/s.

// ANALYSIS

This is a community help thread, not an announcement — but it surfaces a real insight: VRAM alone doesn't determine local LLM performance; system RAM capacity and CPU-GPU memory sharing are equally critical for large MoE models.

  • Qwen3.5-35B-A3B is a Mixture-of-Experts model that only activates 3.5B parameters per token, making it unusually RAM-friendly despite its 35B parameter count
  • The HP Omen Max with RTX 5080 (16GB VRAM) failed while an older RTX 4080 (12GB VRAM) + 64GB system RAM succeeded — demonstrating that total addressable memory matters more than GPU VRAM alone
  • 64GB of system RAM appears to be the threshold that enables this model class on consumer laptops
  • The trend toward CPU-GPU unified or shared memory (seen in Apple Silicon and AMD APUs) may give those platforms an edge for local LLM inference over discrete GPU laptops
// TAGS
llminferenceedge-aiopen-sourceqwen3.5-35b-a3b

DISCOVERED

74d ago

2026-03-15

PUBLISHED

74d ago

2026-03-15

RELEVANCE

5/ 10

AUTHOR

SnooOnions6041