Agents-A1-4B, a new model developed by InternScience, demonstrates strong performance across various benchmarks, particularly in long-horizon search and agentic tasks. The model, which is based on Qwen3.7-4B, significantly outperforms its base model in areas like BrowseComp and GAIA. While it shows competitive results in instruction following and engineering tasks, it lags behind larger models in some areas like LiveCodeBench-V6 and FrontierScience-Research. AI
IMPACT This model's performance in long-horizon search and agentic tasks could inform future developments in AI agents and complex problem-solving.
RANK_REASON The item describes a new model release with benchmark results, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]
- Agents-A1-4B
- BrowseComp
- FrontierScience-Research
- InternScience
- LiveCodeBench-V6
- Qwen3.5-4B
- Qwen3.7-4B
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
