Qwen vs DeepSeek: Versatility vs Visible Reasoning

Qwen3.5 and Qwen3.6 are versatile all-rounders, while DeepSeek built its name on visible chain-of-thought reasoning. DeepSeek R1 distills run locally on modest Macs, and the newer DeepSeek V4 generation ships open weights. The practical question is what each family offers at your RAM budget.

Models5 categories compared

Verdict

Qwen

Qwen is the better daily driver on most Macs, with current-generation models from 2 GB to 96 GB of RAM. DeepSeek R1 distills remain the pick for step-by-step reasoning, and the 7B distill needs just 10 GB. DeepSeek V4 Flash is open weight but wants a 128 GB Mac, so it stays niche locally.

Qwen

wins

Ties

draws

DeepSeek

wins

Category-by-Category Breakdown

Category	Qwen	DeepSeek	Winner
Visible Reasoning	Strong reasoning, especially Qwen3.6 27B	R1 distills show their full chain-of-thought	DeepSeek
Everyday Coding & Chat	Qwen3.5 and 3.6 cover chat, coding, and agents	R1 distills are specialized, V4 is mostly cloud	Qwen
Response Speed	Direct answers without a thinking preamble	Reasoning tokens come before every answer	Qwen
Current-Generation Local Fit	Qwen3.5/3.6 run on 8-24 GB Macs	DeepSeek V4 Flash needs a 128 GB Mac	Qwen
RAM for Small Reasoning Models	Qwen3.5 9B: 14 GB min RAM	R1 7B distill: 10 GB min RAM	DeepSeek

Detailed Analysis

Visible Reasoning

DeepSeek

DeepSeek R1 was trained to reason step-by-step and exposes its thinking. For math, logic, and tricky debugging, that transparency still wins.

Qwen

Strong reasoning, especially Qwen3.6 27B

DeepSeek

R1 distills show their full chain-of-thought

Everyday Coding & Chat

Qwen

Qwen is the stronger generalist. DeepSeek's local distills shine on reasoning but are not the best pick for quick chat or translation.

Qwen

Qwen3.5 and 3.6 cover chat, coding, and agents

DeepSeek

R1 distills are specialized, V4 is mostly cloud

Response Speed

Qwen

R1-style models spend tokens on their thinking chain first. The same question takes noticeably longer to finish than with Qwen.

Qwen

Direct answers without a thinking preamble

DeepSeek

Reasoning tokens come before every answer

Current-Generation Local Fit

Qwen

Qwen's latest generation targets ordinary laptops. DeepSeek's latest open release is a 284B MoE that only fits very large Mac Studios.

Qwen

Qwen3.5/3.6 run on 8-24 GB Macs

DeepSeek

DeepSeek V4 Flash needs a 128 GB Mac

RAM for Small Reasoning Models

DeepSeek

The R1 7B distill is the lighter option, loading 5.5 GB. It is the cheapest way to get chain-of-thought reasoning on a Mac.

Qwen

Qwen3.5 9B: 14 GB min RAM

DeepSeek

R1 7B distill: 10 GB min RAM

Frequently Asked Questions

Can I run DeepSeek V4 locally on a Mac?

Only on very large machines. V4 Flash is open weight under MIT, a 284B MoE with 13B active parameters, and needs a 128 GB Mac via a llama.cpp fork. Most users should run the R1 distills instead.

Which should I run on a 16 GB MacBook?

Qwen3.5 9B for general use. Switch to `ollama run deepseek-r1:7b` when you want visible reasoning. The R1 7B distill needs 10 GB minimum, which leaves headroom on a 16 GB machine.

Why is DeepSeek R1 slower than Qwen?

R1 models generate a thinking process before the actual answer. That means more tokens per response and longer wall-clock times, even when raw token speed is similar.