Multipl-E MBPP
MultiPL-E extends the Mostly Basic Python Problems (MBPP) benchmark to 18+ programming languages for evaluating multilingual code generation capabilities. MBPP contains 974 crowd-sourced programming problems designed to be solvable by entry-level programmers, covering programming fundamentals and standard library functionality. Each problem includes a task description, code solution, and automated test cases.
Llama 3.1 405B Instruct from Meta currently leads the Multipl-E MBPP leaderboard with a score of 0.657 across 3 evaluated AI models.
Llama 3.1 405B Instruct leads with 65.7%, followed by Llama 3.1 70B Instruct at 62.0% and Llama 3.1 8B Instruct at 52.4%.
Progress Over Time
Interactive timeline showing model performance evolution on Multipl-E MBPP
Multipl-E MBPP Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | 405B | 128K | $0.89 / $0.89 | |||
| 2 | 70B | 128K | $0.20 / $0.20 | |||
| 3 | 8B | 131K | $0.03 / $0.03 |
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