Model overview
This model is a fine-tuned version of ModernBERT-large for binary classification of human-written vs. AI-generated text. It outputs a single probability, P(AI), indicating the likelihood that a given input was generated by a language model. Vanguard AI-text detector was part of the 2nd-place system at PAN-CLEF 2026's Voight-Kampff Generative AI Detection leaderboard. This model was trained on approximately 1.1 million texts from three datasets: DACTYL 2.0, LLMTrace, and MAGA-Bench. The model was evaluated against two leading open-source AI text detectors, Fakespot and Desklib, across ten benchmark datasets. Three of these (dactyl-v2.0, llm-trace-eng, maga) are in-distribution with respect to this model's training data; the remaining seven (beemo, coconuts, detectrl, dolly-cosmopedia, originalityai, realdet, uchicago) are out-of-distribution and were not seen during training.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
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Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。