DeepSeek Chinese white-collar tasks evaluation
DeepSeek-V4-Pro 53% Agents complete 30 Chinese professional analysis, document generation and editing tasks across 13 industries. Blind human annotators compare outputs against a baseline model.
In-house DeepSeek evaluation. The prompts are not public.
- Made by
- DeepSeek
- Released
- April 2026
- Kind
- Documents and spreadsheets
- Level
- Expert
- Scored
- Ranked by votes
- Answers
- Agent task
- Tasks
- Kept private
- Strongest model tested
- DeepSeek-V4-Pro #69 on the capability index
- Last in a system card
- April 2026
- Last model added
- April 2026
Only DeepSeek-V4-Pro has a rating here, from its lab’s own post
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs. A rating ranks a model only against others rated in the same arena at the same time, so these don’t show who leads.
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | DeepSeek-V4-Pro | 53% | Apr 2026 | Lab model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Apr 26, 2026 | DeepSeek-V4-Pro technical report | 53 | Chinese white-collar tasks, overall win rate vs Opus-4.6-Max, tie 10.0, lose 37.0, non-loss 63 (Figure 11). Figure 12 dimension scores are printed but not labeled by model | Capabilities |
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