TaskEvolving Deep Research (No Tools, Without Hints): leaderboard

TaskEvolving (Wang, Chen et al., 2026) evolves 500 NQ-Open questions into verifiable deep research tasks, each a graph of atomic steps with fact-grounded rubric checkpoints scored by a Qwen3.7-Max judge. In this setting the model answers from its own knowledge without tools and receives a short everyday question that hides those constraints. Score is the percentage of rubric points met; higher is better.

Metric: Rubric score (%; fact-grounded pointwise checkpoints of 500 evolved deep research tasks, evidential plus analytical, judged by Qwen3.7-Max; model mode without tools, internal knowledge only; query without hints: a short everyday question). Source: arxiv.org. Saturation forecast: Around February 2027. 10 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.6 Terra54#60
2Gemini 3.5 Flash52#98
3GLM-5.252#137
4DeepSeek V4 Pro48#181
5Claude Sonnet 547#108
6Qwen 3.7 Max47#142
7MiniMax-M2.531#590
8Qwen 3.6 Flash28#422
9Qwen 3 32B18#960
10Qwen 3 14B16#1235

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=taskevolving-deep-research-no-tools-without-hints · How It Works · Data refreshed daily, snapshot 2026-11-12.