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
LiveCodeBench is a holistic and contamination-free evaluation benchmark for large language models for code. It continuously collects new problems from programming contests (LeetCode, AtCoder, CodeForces) and evaluates four different scenarios: code generation, self-repair, code execution, and test output prediction. Problems are annotated with release dates to enable evaluation on unseen problems released after a model's training cutoff.
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.
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Gemini 2.5 Pro | 0.756 | Not recorded | Not recorded | 2025-05-20 · model_announcement | LLM Stats |
| Gemini 2.5 Flash | 0.639 | Not recorded | Not recorded | 2025-05-20 · model_announcement | LLM Stats |
| Qwen3 VL 235B A22B Instruct | 0.614 | Not recorded | Not recorded | 2025-09-22 · model_announcement | LLM Stats |
| MiniCPM-SALA | 0.6048 | Not recorded | Not recorded | 2026-02-11 · model_announcement | LLM Stats |
| Gemini 2.0 Flash-Lite | 0.289 | Not recorded | Not recorded | 2025-02-05 · model_announcement | LLM Stats |
| Gemma 3n E4B Instructed | 0.257 | Not recorded | Not recorded | 2025-06-26 · model_announcement | LLM Stats |
| Gemma 3n E4B Instructed LiteRT Preview | 0.257 | Not recorded | Not recorded | 2025-05-20 · model_announcement | LLM Stats |
| Gemma 3n E2B Instructed | 0.186 | Not recorded | Not recorded | 2025-06-26 · model_announcement | LLM Stats |
| Gemma 3n E2B Instructed LiteRT (Preview) | 0.186 | Not recorded | Not recorded | 2025-05-20 · model_announcement | LLM Stats |