| --- |
| language: |
| - ne |
| - en |
| license: apache-2.0 |
| tags: |
| - evaluation |
| - benchmark |
| - nepali |
| - low-resource |
| - nlp |
| pretty_name: NepaliBench |
| size_categories: |
| - n<1K |
| task_categories: |
| - question-answering |
| - text-classification |
| - text-generation |
| --- |
| |
| # NepaliBench 🏔️ |
|
|
| A rigorous evaluation benchmark for Nepali language models. |
|
|
| ## Why this exists |
|
|
| There is no standard, publicly reproducible benchmark for evaluating |
| Nepali LLMs. This dataset was created after a systematic evaluation of |
| himalaya-ai's NanochatGPT and Gemma fine-tune revealed that models |
| claiming Nepali capability had no shared evaluation standard to measure |
| against. |
|
|
| ## Dataset |
|
|
| 100 carefully curated evaluation examples across 8 categories: |
|
|
| | Category | Code | Count | Description | |
| |---|---|---|---| |
| | Nepali Factual Knowledge | FACT | 20 | Geography, history, constitution, symbols | |
| | Nepali Cultural Knowledge | CULT | 15 | Festivals, ethnic traditions, proverbs | |
| | Nepali Language Competence | LANG | 15 | Grammar, script, translation | |
| | Mathematical Reasoning | MATH | 15 | Arithmetic in Nepali cultural context (mana/pathi, ropani, bigha) | |
| | Logical Reasoning | REASON | 10 | Syllogisms, analogies, sequences | |
| | Instruction Following | INST | 10 | Format compliance, length constraints | |
| | Nepali NLP Tasks | NLP | 10 | NER, sentiment, summarization, language ID | |
| | Safe Behavior | SAFE | 5 | Appropriate refusal, uncertainty acknowledgment | |
|
|
| ## Schema |
|
|
| ```json |
| { |
| "id": "NB-FACT-001", |
| "category": "Nepali Factual Knowledge", |
| "subcategory": "geography", |
| "prompt_ne": "सगरमाथाको उचाइ कति छ?", |
| "prompt_en": "What is the height of Mount Everest?", |
| "reference_answer_ne": "८,८४८.८६ मिटर", |
| "reference_answer_en": "8,848.86 meters", |
| "difficulty": "easy", |
| "answer_type": "exact", |
| "rubric": null, |
| "verified_source": "Nepal-China Joint Survey 2020", |
| "tags": ["geography", "everest", "height"] |
| } |
| ``` |
|
|
| ## Answer Types |
|
|
| - `exact` — model answer must match reference exactly (or contain exact figure) |
| - `contains` — model answer must contain key information from reference |
| - `rubric` — model answer evaluated against rubric criteria |
|
|
| ## Design Principles |
|
|
| - All FACT answers verified against official sources (Nepal Government, UN records, Constitution of Nepal 2072) |
| - Regional diversity: Madhesh/Terai culture explicitly represented (Chhath, Tharu Maghi, Maithili language) |
| - Nepali unit systems used in MATH (mana/pathi, ropani/aana, bigha/kattha) |
| - Difficulty genuinely distributed: 41% easy, 40% medium, 19% hard |
|
|
| ## Origin |
|
|
| Created as part of an independent audit of himalaya-ai's Nepali AI |
| model ecosystem (June 2026). Two PRs were filed against himalayagpt-0.5b |
| and himalayagpt-0.5b-it fixing critical GenerationMixin bugs discovered |
| during evaluation. |
|
|
| ## Author |
|
|
| Premanand Pathak (premmm) — AI Engineer, Kathmandu, Nepal |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{pathak2026nepalibench, |
| author = {Premanand Pathak}, |
| title = {NepaliBench: A Benchmark for Nepali Language Model Evaluation}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| url = {https://huggingface.co/datasets/premmm/nepali-bench} |
| } |
| ``` |
|
|
