NitiBench+ - RAG In-force: leaderboard

NitiBench+ Table 17:500 held-out Thai legal questions; three distinct evidence settings. Bar-standard answer scores 0–10; citation precision/recall/F 1 fractions 0–1. avg@3 for 13 self-hosted bf 16 models; other rows are leaderboard API observations, not replicated avg@3. AppendixC exact checkpoints and reasoning-on controls retained; other API effort unspecified. Same official judging rubric; citations checked against current in-force law. The public live site was 403, resolved via complete native paper table. Metric: Bar-standard score (0–10).

Metric: Bar-standard score (0–10). Source: arxiv.org. Saturation forecast: Around February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Claude Fable 5.17.78#10
2Gemini 4 Argon7.54#9
3GPT-6.1 Sol7.28#7
4Claude Opus 5.57.03#3
5DeepSeek V4.1 Flash6.39#37
6Muse Spark 1.36.37#31
7GPT-6.1 Terra6.14#15
8Claude Sonnet 5.55.97#14
9DeepSeek V4 Flash5.71#155
10Qwen 3.8 27B5.48#123
11Claude Haiku 5.54.62#43
12Gemma 4 31B (IT) (Thinking)4.57#178 (Gemma 4 31B (IT))
13gemma-4-26B-A4B-it (Thinking)3.68
14NVIDIA-Nemotron-3-Super-120B-A12B-BF16 (Thinking)3.23#394 (NVIDIA-Nemotron-3-Super-120B-A12B-BF16)
15Qwen 3 8B0.96#678

No result here: #6 GPT-6 Astra.

Interactive version: theaggregate.ai/benchmark?slug=nitibench-plus-rag-in-force · How It Works · Data refreshed daily, snapshot 2026-11-05.