Qwen 3.6 35B-A3B @ Q4 or Gemma 4 12B @ Q8?
Summary
User asks for advice on choosing between quantized Qwen 3.6 35B-A3B at Q4 and Gemma 4 12B at Q8 for local codebase work on a 32GB unified memory setup.
Similar Articles
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.
Qwen3.8 vs Qwen3.6 vs Gemma 4 on a 24GB GPU (10 minute read)
This article benchmarks and compares the performance of Qwen3.8-27B, Qwen3.6-27B, and Gemma 4 31B on a 24GB GPU, recommending Qwen3.8-27B as the best default for most users due to superior coding and reasoning capabilities.
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.
gemma-4-12b-it vs Qwen3.5-9B on shared benchmarks: Qwen is overall winner beating gemma in 5/8 benchmarks despite a smaller footprint
Qwen3.5-9B outperforms gemma-4-12b-it on 5 of 8 benchmarks despite having a smaller footprint, with gemma only slightly better at coding.
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.