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Llama 3.1-8B benchmark results
8 results on 8 benchmarks from 5 sources.
Also listed as: llama-3.1-8b-instruct · Llama-3.1-8B-Instruct · Llama 3.1 Instruct Turbo (8B) · Llama-3.1-8B-Instruct (Prompt) · Llama-3.1-8B · meta-llama/Llama-3.1-8B-Instruct · meta-llama/Llama-3.1-8B
All benchmark results
| Benchmarks | Score | Rank | Setting | Source type | Date |
|---|---|---|---|---|---|
| LMArena Text | 1211 | 341 | Overall, style control on; 49605 votes; 95% CI 1207–1215“llama-3.1-8b-instruct” | Official leaderboard | Oct 8, 2026 |
| Open LLM Leaderboard v2 | 23.8% | 1905 | Average of 6 normalised benchmarks; float16; 8.03B params“meta-llama/Llama-3.1-8B-Instruct” | Official leaderboard | Mar 13, 2025 |
| GPQA Diamond | 27.0% | 270 | Epoch AI run, accuracy | Independent run | Aug 27, 2026 |
| MMLU | 56.1% | 76 | Exact match; 5-shot | Official leaderboard via Epoch AI | Jul 23, 2024 |
| MMLU-Pro | 36.6% | 204 | Overall accuracy; data source: TIGER-Lab; 8B“Llama-3.1-8B” | Official leaderboard | Mar 11, 2026 |
| AIME (OTIS Mock AIME 2024–2025) | 1.7% | 253 | Epoch AI run, OTIS Mock AIME 2024–2025 | Independent run | Aug 27, 2026 |
| MATH Level 5 | 22.9% | 84 | Epoch AI run, accuracy | Independent run | Jan 27, 2025 |
| BFCL v4 (function calling) | 25.8% | 85 | Overall accuracy; prompt-based“Llama-3.1-8B-Instruct (Prompt)” | Official leaderboard | Oct 17, 2026 |
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FAQ
Where do these Llama 3.1-8B scores come from?
From Epoch AI Benchmarking Hub, Berkeley Function Calling Leaderboard (BFCL), LMArena leaderboard dataset, MMLU-Pro leaderboard (TIGER-Lab), and Hugging Face Open LLM Leaderboard v2 (archived). Each row links to the original leaderboard, dataset or report, and vendor-reported numbers are labelled.