dQwen3.5 Release - Full-canvas - MBPP+: leaderboard

Base diffusion-model checkpoints; AR comparators follow the exact original publisher paths in the source manifest, including post-trained unsuffixed Qwen3.5 artifacts; 50B/100B adaptation tokens are distinct SWA trained checkpoints, never effort switches. Full-canvas/block decoding are separate boards; one token per step. MMLU5-shot likelihood; GSM8K8-shot1319; MATH5004-shot; HumanEval0-shot164; MBPP3-shot500; MBPP+3-shot378. No fewshot-dlms resampling fusion. Metric: Accuracy (%). Higher is better. Source: https://arxiv.org/html/2609.20751v1

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 21 models tracked.

Top models

#ModelScoreOverall rank
1Qwen2.5-Coder-7B (dQwen release AR checkpoint)71.43
2Qwen2.5-7B (dQwen release AR checkpoint)69.84
3Dream-Coder-7B (Base)65.08
4Qwen3.5-9B (dQwen release AR checkpoint)63.76
5dQwen3.5-9B-Base (50B adaptation tokens)58.2
6Dream-7B (Base)57.67
7dQwen3.5-9B-Base (100B adaptation tokens)56.61
8dQwen3.5-4B-Base (50B adaptation tokens)51.32
9dQwen3.5-4B-Base (100B adaptation tokens)50
10Qwen3.5-4B (dQwen release AR checkpoint)48.41

Interactive version: theaggregate.ai/benchmark?slug=dqwen3-5-release-full-canvas-mbpp-plus · How It Works · Data refreshed daily, snapshot 2026-10-17.