1,140 complex Python programming tasks: BigCodeBench
About
1,140 complex Python programming tasks spanning diverse real-world domains requiring multi-library function calls. Two variants: Complete (function completion) and Instruct (natural language to code).
How to read this benchmark
This benchmark uses a scoring system where higher is better. Scores are useful for directional filtering and model shortlisting, not for universal quality ranking.
Interpretation checklist: prefer benchmarks that are closest to your workload style, then validate against the linked model pages for pricing, context window, and provider availability.
Trust when:
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- Model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Don't trust when:
- There is only one benchmark snapshot or the dataset appears stale.
- Benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
Current modeled score band for tracked entries is roughly 50.0 – 46.1.
Window
Apr 14
single timestamp
Mean delta
No trend
need another snapshot
Coverage
6
models in latest snapshot
Leaderboard preview (top 5)
- 1. DeepSeek V350.0
- 2. Llama 4 Maverick 17B49.7
- 3. Qwen2.5-Coder-32B-Instruct49.0
- 4. GPT-4o (2024-11-20)48.0
- 5. GPT-4o Mini (07-18)46.1