AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
LLM Stats
Multipl-E HumanEval
MultiPL-E is a scalable and extensible approach to benchmarking neural code generation that translates unit test-driven code generation benchmarks across multiple programming languages. It extends the HumanEval benchmark to 18 additional programming languages, enabling evaluation of code generation models across diverse programming paradigms and providing insights into how models generalize programming knowledge across language boundaries.
Evaluation context and evidence
- Source
- LLM Stats
- Publisher
- Not recorded
- Benchmark release
- Not recorded
- Collected
- 2026-08-17
- Modality
- text
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 3
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Llama 3.1 405B Instruct | 0.752 | Not recorded | Not recorded | 2024-07-23 · model_announcement | LLM Stats |
| Llama 3.1 70B Instruct | 0.655 | Not recorded | Not recorded | 2024-07-23 · model_announcement | LLM Stats |
| Llama 3.1 8B Instruct | 0.508 | Not recorded | Not recorded | 2024-07-23 · model_announcement | LLM Stats |