Zhipu AI Releases Technical Analysis and Application Prospects of the New Generation Visual Language Model GLM-4.1V-Thinking

On July 2, 2025, leading company in China's artificial intelligence sector, Zhipu AI, officially announced the open-source release of its new generation general visual language model - the GLM-4.1V-Thinking series. This significant technological breakthrough marks a key leap from 'perceptual intelligence' to 'cognitive intelligence' in large models within our country, injecting new vitality into global artificial intelligence development.

I. Technological Innovations and Architectural Design of GLM-4.1V-Thinking

The GLM-4.1V-Thinking series represents cutting-edge technology in the field of visual language models, with its most notable breakthrough being true visual reasoning capabilities. Unlike traditional visual recognition models, this series can deeply understand event logical relationships within complex dynamic images and establish a complete semantic understanding framework rather than merely extracting surface features for matching.

In terms of model architecture, GLM-4.1V-Thinking adopts several innovative designs. Firstly, it breaks through traditional model limitations on input image resolution by utilizing 3D-RoPE (three-dimensional rotational position encoding) technology to efficiently process images with any aspect ratio up to 4K resolution. Secondly, addressing long-standing technical challenges in video understanding, the model introduces a temporal indexing mechanism that significantly enhances temporal modeling capabilities. Notably, despite having only 9 billion parameters in its lightweight version (GLM-4.1V-9B-Thinking), it performs excellently across multiple benchmark tests demonstrating Zhipu AI's profound expertise in model compression and optimization.

I.I Breakthrough Innovation in Multi-stage Training Strategy

The success of GLM-4.1V-Thinking is largely attributed to its innovative multi-stage training strategy. In the pre-training phase, the research team constructed one of the most comprehensive knowledge-intensive datasets to date covering academic corpora high-quality text-image pairs OCR localization data as well as video temporal data across various dimensions particularly noteworthy is that they employed paraphrasing models for systematic optimization ensuring semantic accuracy and richness within training data.

During supervised fine-tuning standardized Chain-of-Thought data formats were utilized guiding coherent interpretable reasoning processes through carefully designed and tags enabling human-like multi-step progressive thinking when handling complex problems thus significantly enhancing output logic reliability.

Reinforcement learning phases introduced an innovative method called Curriculum Sampling Reinforcement Learning (RLCS). This approach dynamically assesses sample difficulty prioritizing medium-difficulty samples resulting in substantial improvements in training efficiency while independent validators tailored for different domains effectively avoid reward hacking issues ensuring balanced development across all professional fields.

II Comprehensive Evaluation & Analysis of Model Performance

In performance evaluations ,GLM - 4 . 1 V - Thinking exhibited remarkable comprehensiveness . In a comprehensive assessment encompassing twenty-eight mainstream benchmark tests ,the lightweight version with nine billion parameters surpassed competing models at similar scales on twenty-three tasks even approaching or exceeding seventy-two billion parameter large-scale models on eighteen tasks . Such efficient performance demonstrates Zhipu AI’s innovation value regarding architectural design methods used during training . n II.I Professional Performance Across Domains n Within STEM fields (Science Technology Engineering Mathematics ) ,GL M - 41 V - Thinking outperformed currently recognized top-tier GPT – four o models during specialized testing such as MMMU-Pro MathVista .This groundbreaking advancement stems primarily from strong symbolic comprehension logical reasoning abilities allowing accurate processing complex mathematical formula derivations physical process modeling tasks . Long document comprehension aspects saw high scores achieved by this model MMLongBench – Doc test outperforming other similar products deriving advantages from grasping deep semantic structures accurately identifying logical relations implicit information achieving genuine understanding beyond mere pattern matching . GUI agents coding task results demonstrated leading performances WebQuest-SingleQA Flame-VLM-Code showcasing unique strengths human-computer interaction automated programming aspects where not only could interface elements’ functional logics be understood but also engineering specification compliant code implementations generated offering new possibilities software development automation. II.I Cross-Domain Generalization Capability Breakthroughs One revolutionary characteristic defining G L M – 41 V – Thinking lies exceptional cross-domain generalization capability studies revealed single domain reinforcement learning trainings notably enhance performances alternative areas like visual positioning GUI assignments indicating established cognitive frameworks transcending simple task-specific pattern recognitions. Utilizing mixed-all joint training strategies further elevated overall performance revealing underlying associations between diverse domain knowledge capturing these connections successfully facilitated authentic cross-domain integration transferabilities.

III Core Technologies: RLCS & Innovative Reward System Designs

Much credit goes towards successful implementation core technologies namely curriculum sampling reinforcement learning(RLCS) adaptive reward systems which together underpin superior performances attained by G L M–41 V–Thinking . III.I Advanced Concepts Behind Curriculum Sampling Reinforcement Learning(RLCS) Through dynamic assessments evaluating difficulties levels associated with each sample RL CS enables intelligent management throughout entire processes involving offline online evaluations adjusting selection strategies based upon current capacities optimizing experiences gained avoiding inefficiencies stemming solely simplistic choices preventing instabilities arising excessively challenging ones encountered instead emphasizing moderate complexities fostering effective growth trajectories respectively. To optimize further iterations developers incorporated techniques including Ratio EMA Dynamic Sampling Expansion forced answering policies whereby former adjusts ratios accordingly latter ensures best attempts provided under duress without evading responses entirely creating stable ecosystems conducive productive outcomes overall . III..II Delicate Designs Underlying Domain Adaptive Reward Systems Addressing prevalent “reward hacking” concerns typical conventional approaches adopted domain-adaptive rewards system wherein distinct validation modules crafted specific types mathematics reasoning OCR interactions GUIs combined rule-based judgments alongside evaluative mechanisms guaranteeing precision relevance feedback loops mitigating biases emerging singular standards imposed evaluation metrics e.g., validating rigorousness deduction sequences versus focusing operational completeness practicality workflows differentiating criteria ensures equitable developments respective specialties involved herein maximized potentialities realized fully exploiting available resources appropriately aligned strategic objectives pursued diligently advancing collective goals harmoniously orchestrated efforts undertaken collaboratively navigating intricate landscapes present today shaping future endeavors ahead collectively united aspirations envisioned collectively driven purposefully forward toward brighter horizons awaiting discovery unfolding gradually over time transforming realities lived experienced shared universally resonating profoundly impacting lives touched positively influenced journeys embarked upon together forging pathways anew exploring realms previously uncharted expanding boundaries endlessly limitless possibilities abound waiting embrace passionately pursuing excellence tirelessly striving attain heights never imagined before becoming reality now possible indeed !