Qwen 3.5 Local Model Review (Is it Good?)

Qwen 3.5's lower-end model is a free, fast local LLM — but it fails at basic reasoning, so don't trust it with anything important.

What the creator actually tested

The review focuses on the smallest Qwen 3.5 variant, described as just under actually under 7 gigabytes, run locally via LM Studio. It loads comfortably into a consumer Nvidia GPU (the host uses an Nvidia 360), and token output is visibly fast on that setup. A larger 22 GB sibling exists but eats enough VRAM that a Mac user needs 36 32 GB of RAM to keep the OS and Chrome running alongside it.

Where it works

For general-knowledge Q&A the model is responsive. Examples shown include I'm on keto. Make me a meal plan., what is the stock market, and what do you know about Wall Street bets — all answered quickly with reasonable output. The creator calls it useful for heartbeat style tasks and for privacy-sensitive users who don't want to send their information outside of a local environment. The framing: foot soldier agents spawned in volume, not a primary brain.

Where it breaks

The signature test is there's a car wash 50 meters away from me should I walk or drive. Non-thinking mode answers walking — wrong, because you can't wash a car that isn't there. Switching on the thinking model makes it worse: it spirals into what's the likely scenario style regression, burns tokens, and still lands on walk. The creator notes Opus and MiniMax routinely get this right and that Qwen was thinking for so long on a question a human answers instantly.

Hardware reality check

Running locally is free, but you're it's just electricity costs. A single GPU just ain't enough for serious workloads — the creator explicitly points to Elon Musk's GPU setup and Anthropic's cluster as the reason paid frontier models feel different.

Verdict in the creator's words

still struggling on some basic questions and I wouldn't really use it on a day-to-day basis. Better than Gemma 3 in their testing, but not by enough to displace a frontier model.