Knowledge · Benchmark profile
A Chinese multitask academic benchmark reported in DeepSeek-V4 base-model evaluations.
Data verified 21 Jul 2026 · Methodology 1.6.0
Benchmark score on Chinese Massive Multitask Language Understanding
DeepSeek V4 Pro Base leads at 90.8%, followed by DeepSeek V4 Flash Base (90.4%).
Visual analysis
Switch between model placement, score distribution and descriptive provider averages. Every view uses the same sourced leaderboard.
2 ranked models · higher is better
| Model | Rank | Provider | Score |
|---|---|---|---|
| DeepSeek V4 Pro Base | #1 | DeepSeek | 90.8% |
| DeepSeek V4 Flash Base | #2 | DeepSeek | 90.4% |
One best score per model · higher is better
| Rank | Model | Provider | License | Evidence use | Score |
|---|---|---|---|---|---|
| #1 | DeepSeek V4 Pro Base deepseek-v4-pro-base | DeepSeek | open | Estimated reference | 90.8% |
| #2 | DeepSeek V4 Flash Base deepseek-v4-flash-base | DeepSeek | open | Estimated reference | 90.4% |
About Chinese Massive Multitask Language Understanding
A Chinese multitask academic benchmark reported in DeepSeek-V4 base-model evaluations. Results stay tied to the exact model variant and evaluation system. Multiple systems for the same model use the best published score on this page; overall Lumina scoring uses the median of ranking-eligible rows.
Open benchmark source ↗FAQ
A Chinese multitask academic benchmark reported in DeepSeek-V4 base-model evaluations.
DeepSeek V4 Pro Base by DeepSeek currently leads with 90.8%.
2 models in the LuminaBench cohort have a qualifying score on this benchmark.
Related
2026 · 10 results · Reference
Artificial Analysis MMLU-Pro2026 · 4 results · Reference
Massive Multitask Language Understanding2020 · 8 results · Reference
Graduate-Level Google-Proof Q&A2023 · 70 results · Reference
SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines2025 · 19 results · Reference
Massive Multitask Language Understanding Professional2024 · 42 results · Reference
