A harder competitive-programming benchmark family built from Codeforces, ICPC, and IOI problems, with quarter-specific public leaderboards and difficulty-aware reporting.
BenchLM mirrors the published score view for LiveCodeBench Pro. GPT-5.4 leads the public snapshot at 87.5% , followed by Gemini 3.1 Pro (82.9%) and Muse Spark (80.0%). BenchLM does not use these results to rank models overall.
GPT-5.4
OpenAI
Gemini 3.1 Pro
Muse Spark
Meta
The published LiveCodeBench Pro snapshot is tightly clustered at the top: GPT-5.4 sits at 87.5%, while the third row is only 7.5 points behind. The broader top-10 spread is 16.8 points, so the benchmark still separates strong models even when the leaders cluster.
5 models have been evaluated on LiveCodeBench Pro. The benchmark falls in the Coding category. This category carries a 20% weight in BenchLM.ai's overall scoring system. LiveCodeBench Pro is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2025
Tasks
Quarter-specific contest programming sets
Format
Competitive programming
Difficulty
High-end contest programming
LiveCodeBench Pro is distinct from the original LiveCodeBench family. It excludes LeetCode, emphasizes stronger contest difficulty, and the official site publishes quarter-specific leaderboards such as 25Q2 with hard, medium, and easy pass rates.
Version
LiveCodeBench Pro 2025
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
A harder competitive-programming benchmark family built from Codeforces, ICPC, and IOI problems, with quarter-specific public leaderboards and difficulty-aware reporting.
GPT-5.4 by OpenAI currently leads with a score of 87.5% on LiveCodeBench Pro.
5 AI models have been evaluated on LiveCodeBench Pro on BenchLM.
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