CRUXEval
CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation) is a benchmark designed to measure how well large language models can reason about, understand, and mentally execute short Python programs.
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CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation) is a benchmark designed to measure how well large language models can reason about, understand, and mentally execute short Python programs.
Claude Sonnet 4.5 is a multimodal large language model (LLM) developed by Anthropic and released on September 29, 2025, which Anthropic described at launch as "the best coding model in the world." It is a…
CodeContests is a competitive programming dataset created by Google DeepMind for training and evaluating machine learning models on algorithmic problem-solving tasks.
LiveCodeBench is a holistic and contamination-free benchmark for evaluating large language models on code, first released in March 2024 by researchers at UC Berkeley, MIT, and Cornell led by Naman Jain.
MBPP (Mostly Basic Python Problems) is a code generation benchmark of 974 crowd-sourced Python programming tasks designed to be solvable by entry-level programmers, introduced by Jacob Austin, Augustus Odena…
Pass@k is the standard metric for evaluating code generation models: it measures the probability that at least one of k generated candidate solutions passes all of a problem's unit tests.
Program synthesis is the task of automatically constructing a program that satisfies a specification expressed at a higher level than the code itself: a logical formula, a set of input-output examples, a…