Overview
This model, heretic-org/Qwen3-4B-Instruct-2507-heretic, is a decensored variant of the original Qwen3-4B-Instruct-2507, developed using the Heretic v1.2.0 tool. It maintains the 4.0 billion parameter count and an impressive 262,144 native token context length from the base Qwen3 model. A key differentiator is its significantly reduced refusal rate, reporting 5 refusals out of 100 compared to the original's 100 out of 100, making it suitable for use cases requiring less content filtering.
Key Capabilities
- Enhanced General Performance: Demonstrates significant improvements in instruction following, logical reasoning, text comprehension, mathematics, science, coding, and tool usage.
- Extensive Knowledge Coverage: Shows substantial gains in long-tail knowledge across multiple languages.
- User Alignment: Offers markedly better alignment with user preferences for subjective and open-ended tasks, leading to more helpful and higher-quality text generation.
- Agentic Abilities: Excels in tool calling, with recommended integration via Qwen-Agent for simplified development.
Performance Highlights
Compared to the original Qwen3-4B-Instruct-2507, this model shows competitive or superior performance across various benchmarks, particularly in:
- Knowledge: Achieves 69.6 on MMLU-Pro and 62.0 on GPQA.
- Reasoning: Scores 47.4 on AIME25 and 80.2 on ZebraLogic.
- Coding: Reaches 35.1 on LiveCodeBench v6 and 76.8 on MultiPL-E.
- Alignment: Scores 43.4 on Arena-Hard v2 and 83.5 on Creative Writing v3.
Good For
- Applications requiring a less restrictive content policy.
- Tasks demanding strong instruction following and logical reasoning.
- Scenarios benefiting from extended context understanding (up to 262K tokens).
- Developers looking for a model with robust tool-calling capabilities.