What do you all think? Can we say qwen 3.6 27b beats gemini 2.5 pro? Or sonnet 3.7? Because when I tested, I found the 27b do better.
Summary
A user asks whether the 27B-parameter Qwen 3.6 model can outperform Gemini 2.5 Pro and Sonnet 3.7 on deep web search, coding, and agentic tasks, and seeks suggestions for the lowest-parameter model that can beat Gemini 2.5 Pro.
Similar Articles
Qwen 3.6 27B kick balls
A user shares their positive experience using Qwen 3.6 27B locally for complex research and coding, finding it outperforms Gemini Pro in career advice and immigration research, while also noting performance issues with Gemma 4 31B.
Qwen3.6-35B-A3B and 9B are officially on the public Terminal-Bench 2.0 leaderboard!
Qwen3.6-35B-A3B and Qwen3.5-9B models are officially on the Terminal-Bench 2.0 leaderboard, with little-coder achieving 24.6% on the 35B variant, surpassing Gemini 2.5 Pro and Qwen3-Coder-480B, while the 9B model shows that sub-10B local models can compete on hard agentic benchmarks.
The Qwen 3.6 35B A3B hype is real!!!
The author benchmarks small local LLMs, highlighting Qwen 3.6 35B A3B for its superior ability to map academic code to research papers compared to models like Gemma 4 and Nemotron 3 Nano.
Gemma 4 beats Qwen 3.5 (UPDATE), and Qwen 3.6 27B + MiniMax M2.7 is the best OpenCode setup
Personal benchmark shows Gemma-4E4B tops for routing, Qwen-3.6 27/30B beats Gemma-4 for coding, and MiniMax M2.7 MXFP4 replaces giant Qwen-3.5 quants in an OpenCode llama-swap workflow.
Layman's comparison on Qwen3.6 35b-a3b and Gemma4 26b-a4b-it
A user compares Qwen3.6 35B-A3B and Gemma 4 26B-A4B-IT running locally on a 16GB VRAM GPU via LM Studio, finding Qwen3.6 produces more detailed outputs while both run at comparable speeds. The post is an informal community comparison using quantized models.