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README.md

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----
-license: mit
----
+---
+license: apache-2.0
+task_categories:
+  - text-classification
+  - question-answering
+language:
+  - en
+tags:
+  - telecommunications
+  - 5G
+  - LLM-evaluation
+  - benchmark
+  - leaderboard
+pretty_name: Open Telco Leaderboard
+size_categories:
+  - n<1K
+---
+
+# Open Telco Leaderboard Dataset
+
+This dataset contains evaluation results from the **Open Telco** benchmark suite, which measures LLM performance on telecommunications-specific tasks.
+
+## Dataset Description
+
+The leaderboard tracks model performance across four specialized telecom benchmarks:
+
+| Benchmark | Description | Samples |
+|-----------|-------------|---------|
+| **TeleQnA** | 10,000 Q&A pairs testing telecom knowledge across lexicon, research, and standards | 10,000 |
+| **TeleMath** | Mathematical reasoning in telecommunications (signal processing, network optimization) | 500 |
+| **TeleLogs** | Root cause analysis for 5G network throughput degradation across 8 failure modes | 1,000+ |
+| **3GPP-TSG** | Classification of technical documents by 3GPP working group (RAN, SA, CT) | 5,000+ |
+
+## Data Schema
+
+The parquet file contains the following columns:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `rank` | int | Model's overall ranking position |
+| `model` | string | Model name (e.g., "gpt-5.2", "claude-opus-4.5") |
+| `provider` | string | Provider name (e.g., "OpenAI", "Anthropic") |
+| `repo` | string | Full model path |
+| `mean` | float | Mean score across all benchmarks |
+| `teleqna` | float | TeleQnA benchmark score |
+| `teleqna_stderr` | float | TeleQnA standard error |
+| `telelogs` | float | TeleLogs benchmark score |
+| `telelogs_stderr` | float | TeleLogs standard error |
+| `telemath` | float | TeleMath benchmark score |
+| `telemath_stderr` | float | TeleMath standard error |
+| `tsg` | float | 3GPP-TSG benchmark score |
+| `tsg_stderr` | float | 3GPP-TSG standard error |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("GSMA/leaderboard")
+df = dataset["train"].to_pandas()
+
+# View top models
+print(df.sort_values("mean", ascending=False).head(10))
+```
+
+## How Results Are Generated
+
+Evaluations are run using the [Inspect AI](https://inspect.ai-safety-institute.org.uk/) framework. The workflow:
+
+1. Models are evaluated against each benchmark
+2. Results are logged as `.eval` files
+3. Scores are aggregated into this parquet file
+4. The leaderboard website displays the rankings
+
+## Related Datasets
+
+- [TeleQnA](https://huggingface.co/datasets/netop/TeleQnA) - Telecom Q&A benchmark
+- [TeleMath](https://huggingface.co/datasets/netop/TeleMath) - Telecom math reasoning
+- [TeleLogs](https://huggingface.co/datasets/netop/TeleLogs) - Network log analysis
+- [3GPP-TSG](https://huggingface.co/datasets/eaguaida/gsma_sample) - 3GPP document classification
+
+## Links
+
+- [Open Telco Website](https://gsma-research.github.io/open_telco/)
+- [GitHub Repository](https://github.com/gsma-research/open_telco)
+
+## License
+
+Apache 2.0

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