TAEF (Text Analytics Evaluation Framework): leaderboard
LLMs have demonstrated exceptional proficiency in a wide range of NLP tasks. However, a notable gap remains in practical data analysis scenarios, particularly when LLMs are required to process long sequences of unstructured documents, such as news feeds or, as specifically addressed in this paper, social media posts. To empirically assess the effectiveness of LLMs in this setting, we introduce a q
Metric: F1 (self-reported). Source: benchmarklist.com. Saturation forecast: Around July 2027. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 3.5 397B A17B | 79.5 | #146 |
| 2 | Grok 4.1 Fast | 77.3 | #217 |
| 3 | Qwen 3.5 122B A10B | 72.2 | #173 |
| 4 | Gemini 3.1 Flash Lite | 70.3 | #191 |
| 5 | GPT-5.4 Mini | 68.7 | #212 |
| 6 | Llama 3.3 70B Instruct | 66.5 | #534 |
| 7 | Llama 3.1 8B Instruct | 65.5 | #1035 |
| 8 | Llama 3.2 3B Instruct | 38.5 | #1352 |
| 9 | Qwen 3 4B Instruct | 33.7 | #657 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=taef-text-analytics-evaluation-framework · How It Works · Data refreshed daily, snapshot 2026-10-20.