Qwen 3.6 27B still curb stomps Deepseek V4 in coding

1. Deepseek V4 is still in preview (training is not finished)

2. Qwen is much more demanding and borderline unusable on consumer hardware because it's a dense model. The 27B parameters are active all time for each token. It's not a MoE architecture where a router activates only some of them.

3. Qwen doesn't like quantization at all.

	▲	kgeist 11 minutes ago \| parent \| next [-]
		I have to disagree with most claims. I run Qwen3.6-27b at 260k context and 40-60 tok/sec. It handles most coding problems as well as Sonnet 4.6 under OpenCode on our production tasks. (As an experiment, I run the same prompts for the same issues in parallel for Qwen 3.6 and Sonnet 4.6 and usually see little difference in performance). I see zero degradation from quantization in practice. Settings: RTX 5090, 5-bit weights (Unsloth), FP8 KV cache. Last time I tried running large MoEs on this PC, they had inferior quality at 2-3 bits compared to much smaller dense models at 5-6 bits, and were slower anyway.
	▲	trollbridge 9 minutes ago \| parent \| prev [-]
		You can run the 35B A3B model which is an MoE. Runs great on a 5090.