Tested on 14 benchmarks · BenchGecko score 54.2. Top scores: CMMLU (89.7%), MMLU (76.5%), Aider — Code Editing (55.6%).
Code editing benchmark from the Aider project. Measures ability to apply targeted code changes while maintaining correctness and style.
Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.
HuggingFace MuSR (Multi-Step Reasoning). Tests multi-hop reasoning requiring chaining multiple facts together.
Competition-level math from AMC, AIME, and olympiad problems. Level 5 is the hardest tier, requiring creative problem-solving.
HuggingFace evaluation of MATH Level 5 problems. Competition math requiring advanced reasoning and proof construction.
- Typetext
- ContextN/A
- ReleasedJan 2024
- LicenseOpen Source
- Statusbenchmark-only
Frequently Asked Questions
Key facts · as of 2026-04-09
- Qwen2-72B by Alibaba Qwen. BenchGecko score 54.2, rank 121 of 312 scored models (normalized average of public benchmark scores).
- List price n/a input · n/a output per 1M tokens (as of 2026-04-09).
How to cite · data as of 2026-04-09
Qwen2-72B · benchmarks, pricing and providers. BenchGecko, data as of 2026-04-09. https://benchgecko.ai/model/qwen2-72b
Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP