Caisi states open models lag behind the American frontier, with the gap widening
The Center for AI Standards and Innovation (CAISI) has evaluated the DeepSeek V4 Pro AI model, finding it to lag behind leading U.S. models by approximately eight months. Despite being the most capable model from the People's Republic of China, its performance on CAISI's benchmarks is lower than its self-reported evaluations. DeepSeek V4 is noted for its cost efficiency compared to similar models, although it still trails behind U.S. counterparts in capability.
- ▪CAISI's evaluation indicates that DeepSeek V4's capabilities lag behind the frontier by about 8 months.
- ▪DeepSeek V4 is the most capable PRC AI model evaluated by CAISI to date across multiple domains.
- ▪The model is more cost efficient than other models of similar capability on most benchmarks.
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| Original publisher | NIST |
| Canonical URL | https://www.nist.gov/news-events/news/2026/05/caisi-evaluation-deepseek-v4-pro |
| Publication time | Thu, 21 May 2026 08:40:04 +0000 |
| Retrieval time | 2026-05-21T08:51:10.385Z |
| Last seen | 2026-05-21T08:51:10.385Z |
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In April 2026, the Center for AI Standards and Innovation (CAISI) evaluated the open-weight AI model DeepSeek V4 Pro (“DeepSeek V4”). CAISI evaluations indicate that DeepSeek V4’s capabilities lag behind the frontier by about 8 months (Figure 1). Figure 1: Comparison of aggregate capabilities over time of the most capable publicly released U.S. and PRC models according to a suite of benchmarks covering five domains.Every 200-point increase on the y-axis equates to a 3x increase in the odds of solving a given task. Model capability was fitted using an approach inspired by Item Response Theory (IRT), as detailed in the Appendix. 16 benchmarks across 35 models were used to produce this figure. Trend lines were fit with least squares regression on frontier models. Error bars denote 95% CIs.
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