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hf_README.md

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----
-dataset_info:
-- config_name: release_v1
-  features:
-  - name: id
-    dtype: int64
-  - name: problem_id
-    dtype: string
-  - name: problem_desc
-    dtype: string
-  - name: time_limit_ms
-    dtype: int64
-  - name: memory_limit_MB
-    dtype: int64
-  - name: checker
-    dtype: string
-  - name: test_cases
-    list:
-    - name: input
-      dtype: string
-    - name: output
-      dtype: string
-  data_files:
-  - split: test
-    path: release_v1/test_50375e15.parquet
-license: cc-by-4.0
-language:
-- en
-tags:
-- benchmark
-- competitive-programming
-task_categories:
-- text-generation
----
-# CF-Div2-Step Evaluation Benchmark
-
-## Introduction
-
-We introduce **CF-Div2-Stepfun**, a dataset curated to benchmark the competitive programming capabilities of Large Language Models (LLMs). We evaluate our proprietary **Step 3.5 Flash** ([visit website](https://static.stepfun.com/blog/step-3.5-flash/)) alongside several frontier models on this benchmark.
-
-The benchmark comprises 53 problems sourced from official CodeForces Division 2 contests held between September 2024 and February 2025. We develop an offline evaluation framework that utilizes a local grading mechanism as an alternative to real-time online submissions.
-
-The generated test cases consist of:
-
-- Small-scale test cases, for initial functional verification.
-- Randomized large-scale data, for performance and complexity verification.
-- Handcrafted edge cases, derived from common error patterns and "hacked" submissions from real contest participants.
-- Automated stress testing data, generated by stress testing technique, which keeps generating test cases until one can distinguish failed submissions from correct submissions.
-
-To validate the reliability of this benchmark, we run both correct and representative failed submissions from the original contests. Our evaluator correctly identify 100% of the accepted submissions as "Passed," while 92.45% of the failed submissions are accurately flagged.
-
-## Quickstart
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("stepfun-ai/CF-Div2-Stepfun", name="release_v1", split="test")
-```
-
-## Evaluation Details
-
-The evaluation results are shown below.
-
-| Model | C++ (avg@8) | Python (avg@8) | Java (avg@8) | C++(pass@8 rating) |
-| Step 3.5 Flash | **86.1%** | **81.5%** | 77.1% | **2489** |
-| Gemini 3.0 Pro | 83.5% | 74.1% | **81.6%** | 2397 |
-| Deepseek V3.2 | 81.6% | 66.5% | 80.7% | 2319 |
-| GLM-4.7 | 74.1% | 63.0% | 70.5% | 2156 |
-| Claude Opus 4.5 | 72.2% | 68.4% | 68.9% | 2100 |
-| Kimi K2-Thinking | 67.9% | 60.4% | 58.5% | 1976 |
-| Minimax-M2.1 | 59.0% | 46.4% | 58.0% | 1869 |
-| Mimo-V2 Flash | 46.9% | 43.6% | 39.6% | 1658 |
-
-We use the following prompt for all model evaluations:
-
-```
-You are a coding expert. Given a competition-level coding problem, you need to write a {LANGUAGE} program to solve it. You may start by outlining your thought process. In the end, please provide the complete code in a code block enclosed with ``` ```.
-{question}
-```
-
-The compilation and execution commands for C++, Python, Java are given below:
-
-```
-g++ -std=c++20 -fno-asm -fsanitize=bounds -fno-sanitize-recover=bounds –static -O2 -DONLINE_JUDGE -o code.exe code.cpp
-./code.exe
-```
-
-```
-python3 code.py
-```
-
-```
-javac -J-Xmx544m {JAVA_CLASS_NAME}.java
-java -XX:+UseSerialGC -Xmx544m -Xss64m -DONLINE_JUDGE {JAVA_CLASS_NAME}
-```
-
-For Python and Java evaluation, we use a double time limit.
-
-The benchmark kits follow the [testlib](https://github.com/MikeMirzayanov/testlib) pipeline in validation and evaluation. There is a validator for each problem to check test case integrity, and a specific checker to verify output correctness.
-
-The rating evaluation follows [CodeELO](https://arxiv.org/abs/2501.01257) methodology. For pass@8 metrics, we calculate the expected score with a fail-penalty but no time-penalty.
-
-## License
-
-We are releasing the benchmark under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license.
-
-## Citation
-
-If you find CF-Div2-Step useful, please consider citing it as: