Model card
Llama 3.1 70B.
Metaopen-source
§ 02 · Benchmarks
Every benchmark Llama 3.1 70B has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | HumanEval | Computer Code · Code Generation | pass@1 | 80.5% | #36 | — | source ↗ |
| 02 | MATH | Reasoning · Mathematical Reasoning | accuracy | 68.0% | #37 | — | source ↗ |
| 03 | MMLU | Reasoning · Commonsense Reasoning | accuracy | 82.0% | #48 | — | source ↗ |
| 04 | GPQA Diamond | Reasoning · Multi-step Reasoning | accuracy | 41.7% | #71 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where Llama 3.1 70B actually performs.
§ 05 · Related models
Other Meta models scored on Codesota.
Llama 4 Maverick
400B total / 17B active (128 experts) params · 15 results
Llama 3.1 405B
13 results
Llama 3 70B
11 results
Llama 3 (405B, Instruct)
9 results
Llama-3.2-1B-Instruct
9 results
Llama-3.2-3B-Instruct
9 results
Llama-4-Scout
109B total / 17B active (16 experts) params · 9 results
Meta-Llama-3.1-405B-Instruct
9 results
§ 06 · Sources & freshness
Where these numbers come from.
openai-simple-evals
4
results
0 of 4 rows marked verified.