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- **INF-Retriever-v1-1.5B** is a lightweight version of the **INF-Retriever-v1**, an LLM-based dense retrieval model developed by INF TECH. It is built upon the gte-Qwen2-1.5B-instruct model and specifically fine-tuned to excel in retrieval tasks, particularly for Chinese and English data. - As of February 19, 2025, **INF-Retriever-v1-1.5B** ranks both **No.1** on the Automated Heterogeneous Information Retrieval Benchmark of version 24.04 & 24.05(AIR-Bench) for the bilingual Chinese and English sub-leaderboard, among models with fewer than 7B parameters. This demonstrates its cutting-edge performance in heterogeneous information retrieval tasks. - **Optimized for Chinese and English retrieval**: The model has been specifically fine-tuned with retrieval-focused datasets in both languages, significantly improving its accuracy and efficiency for a variety of retrieval scenarios.

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We are excited to release Infinity-Parser2, our latest flagship document understanding model. We offer two distinct variants to address diverse deployment constraints: Infinity-Parser2-Pro, optimized for maximum accuracy in precision-critical tasks, achieves state-of-the-art results on olmOCR-Bench (87.6%) and ParseBench (74.3%), surpassing frontier models including DeepSeek-OCR-2, PaddleOCR-VL-1.5, and MinerU2.5. Infinity-Parser2-Flash, engineered for low-latency inference, delivers a 3.68x speedup over our previous Infinity-Parser-7B model. With significant upgrades to both our data engine and multi-task reinforcement learning approach, the model consolidates robust multi-modal parsing capabilities into a unified architecture, unlocking brand-new zero-shot capabilities across a wide range of real-world business scenarios. Task Infinity-Parser2-Pro Infinity-Parser2-Flash PaddleOCR-VL-1.5 DeepSeek-OCR-2 MinerU2.5 Gemini-3-Pro Note: '*' denotes results evaluated using our internal evaluation tools. '‡' denotes results from the Gemini-3.1-Pro.

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Paper Link 👁️ --> 🏠 Home Page &nbsp&nbsp | &nbsp&nbsp 🤗 Model &nbsp&nbsp | &nbsp&nbsp 📊 Dataset &nbsp&nbsp | &nbsp&nbsp 📄 Paper &nbsp&nbsp | &nbsp&nbsp 🚀 Demo &nbsp&nbsp **OpenCoder** is an open and reproducible code LLM family which includes 1.5B and 8B base and chat models, supporting both English and Chinese languages. Starting from scratch, OpenCoder is pretrained on 2.5 trillion tokens composed of 90% raw code and 10% code-related web data, and supervised finetuned on over 4.5M high-quality SFT examples, finally reaching the performance of top-tier code LLMs. We provide not only model weights and inference code, but also the reproducible training data, the complete data processing pipeline, rigorous experimental ablation results, and detailed training protocols. Empowering researchers to build and innovate, OpenCoder is your open foundation for advancing code AI. OpenCoder series (including Base and Chat) support commercial applications under a permissive License.

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