# RTP-LX Completion ![Category](https://img.shields.io/badge/Category-Multilingual%20Safety-1f6feb) ![Metric](https://img.shields.io/badge/Metric-F1%20Score-2da44e) ![Saturation](https://img.shields.io/badge/Saturation-Medium-d29922) [![Paper](https://img.shields.io/badge/Paper-arXiv%202404.14397-b31b1b)](https://arxiv.org/abs/2404.14397) [![GitHub](https://img.shields.io/badge/GitHub-microsoft%2FRTP--LX-181717?logo=github&logoColor=white)](https://github.com/microsoft/RTP-LX) > **Quick answer:** RTP-LX Completion measures multilingual toxicity classification on model-generated completions (rather than prompts) across roughly 28 languages, using Microsoft's human-transcreated extension of RealToxicityPrompts. ## At a Glance **What it tests:** Whether a classifier correctly flags toxic model completions across a broad multilingual set, given a prompt that elicited the completion. **Why it matters:** Completion-level toxicity classification tests whether a model's actual generated text is toxic — a downstream signal that complements prompt-level filtering, particularly relevant for open-ended generation products deployed across many locales. **Known limitations:** Same per-language coverage caveats as RTP-LX Prompt — some languages have less representative data than others. ## What RTP-LX Completion Measures Using the same ~28-language RTP-LX corpus, this task scores classifier judgments on model completions rather than prompts — testing whether toxicity detection generalizes to generated text across the covered language set. ## Benchmark Specifications | Field | Value | |---|---| | Task category | Safety / multilingual toxicity | | Metric | F1 score (%) | | Languages | ~28 | | Created by | Adrian de Wynter, Ishaan Watts, Nektaria Potha, and colleagues (Microsoft) | | Paper | [RTP-LX (arXiv 2404.14397)](https://arxiv.org/abs/2404.14397) | | GitHub | [microsoft/RTP-LX](https://github.com/microsoft/RTP-LX) | | License | Research use (see repository terms) | ## How RTP-LX Completion Is Scored Each completion's ground-truth toxicity label is compared against a classifier's prediction and scored as F1, aggregated across the covered languages. ## State-of-the-Art Results Scores from the Shieldstral model card (Mistral AI, August 2026). F1 (%). | Rank | Model | Score | Source | Date | |---|---|---|---|---| | 1 | [Nemotron-3.5-Content-Safety-4B](/models/nvidia/nemotron-3-5-content-safety-4b) | **95.9%** | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | | 2 | [GPT-OSS-Safeguard-20B](/models/openai/gpt-oss-safeguard-20b) | 94.6% | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | | 3 | [Qwen3Guard-8B](/models/alibaba/qwen3guard-8b) | 93.9% | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | | 4 | [Shieldstral 1.0](/models/mistral-ai/shieldstral-1-0) | 93.5% | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | | 5 | [ShieldGemma-9B](/models/google/shieldgemma-9b) | 79% | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | | 6 | [LlamaGuard-4-12B](/models/meta/llamaguard-4-12b) | 66.5% | [Mistral AI model card](https://huggingface.co/mistralai/Shieldstral-1.0-3B) | 2026-08 | *Scores sourced from Mistral AI's published model card, shown for context. Not Benchgen measurements.* ## RTP-LX Completion on Benchgen > No Benchgen results yet — [be the first to run RTP-LX Completion](/benchmarks/microsoft/rtp-lx-completion). ## RTP-LX Completion vs Other Benchmarks | Benchmark | What it tests | Languages | Saturation | |---|---|---|---| | **RTP-LX Completion** | Multilingual completion toxicity | ~28 | Medium | | RTP-LX Prompt | Multilingual prompt toxicity | ~28 | Medium | | PolyGuard Response | Multilingual response-harm classification | 17 | Medium | ## Run RTP-LX Completion on Your Model Benchgen tracks version-controlled, regression-tested guard-model performance — submit your classifier's RTP-LX completion scores to compare against Shieldstral and other guard models. ## Related Models & Benchmarks - Models: [Shieldstral 1.0](/models/mistral-ai/shieldstral-1-0) · [GPT-OSS-Safeguard-20B](/models/openai/gpt-oss-safeguard-20b) - Benchmarks: [RTP-LX Prompt](/benchmarks/microsoft/rtp-lx-prompt) · [PolyGuard Response](/benchmarks/toxicityprompts/polyguard-response) ## Frequently Asked Questions

What is RTP-LX Completion?

It's the completion-toxicity classification task on Microsoft's RTP-LX benchmark, testing whether a classifier can flag toxic model-generated text across roughly 28 languages.

How is this different from RTP-LX Prompt?

RTP-LX Prompt scores toxicity in the user's input; RTP-LX Completion scores toxicity in the model's generated output for that input.

Who created RTP-LX?

Researchers at Microsoft (de Wynter et al., 2024).

--- *Last updated 2026-08-12.*

Rank	Model	Score
1	nemotron-3-5-content-safety-4b	95.9
2	gpt-oss-safeguard-20b	94.6
3	qwen3guard-8b	93.9
4	shieldstral-1-0	93.5
5	shieldgemma-9b	79
6	llamaguard-4-12b	66.5

RTP-LX Completion — Results

RTP-LX Completion — Evaluations