Welcome to the forefront of the AI maritime era! While everyone is still cheering for every update of GPT, a fierce competition for the AI throne in the Chinese-speaking world has quietly entered a white-hot phase. Are you curious about which domestic models are gearing up to disrupt the current landscape beneath the seemingly calm surface? Do you want to know how much today’s AI can reliably serve as our “intelligent agent” in solving complex problems, beyond just vague conversations? This benchmark evaluation report for Chinese large models in the first half of 2025 will use the most precise data and sharp insights to cut through the fog of technical promotion and take you directly to the ultimate showdown that concerns the future. Are you ready? Let’s reveal who the true king of Chinese AI is!
Below is sharedbythe SuperCLUE team:“Chinese Large Model Benchmark Evaluation Report for the First Half of 2025”The field of Chinese large models in the first half of 2025 is characterized by a flourishing and competitive landscape. This SuperCLUE evaluation report conducts a multi-dimensional and systematic assessment of 45 mainstream large models from both domestic and international sources, revealing the latest patterns in the development of Chinese large models. The report shows that while overseas leading models maintain an advantage in overall capabilities, domestic large models are rapidly catching up, especially demonstrating significant advantages and great potential in areas such as agents, hallucination control, and the open-source ecosystem. The evaluation system covers six core dimensions: mathematical reasoning, scientific reasoning, code generation, agents, precise instruction adherence, and hallucination control, and combines indicators such as cost-effectiveness and overall performance to comprehensively depict the characteristics and market positioning of different models. Overall, the gap in general Chinese capabilities between domestic and international large models is gradually narrowing, with domestic models already possessing global competitiveness in specific application scenarios, as the entire industry transitions from a technological explosion phase to a new stage of deep reasoning and agent exploration.
# 01 Report Summary
Dynamic Changes in Model Capability Gaps
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Overall Gap Continues to Narrow: The report points out that since May 2023, the gap in general Chinese capabilities between the first-tier domestic large models and the top overseas models has shown a clear trend of narrowing. Taking the SuperCLUE general benchmark evaluation as an example, the gap ratio has fluctuated down from an initial 30.12% and has narrowed to 7.78% in the latest evaluation in July 2025. This indicates that domestic manufacturers have made significant achievements in model iteration, technical optimization, and data accumulation, rapidly catching up to international advanced levels.
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Overseas Models Still Hold Significant Advantages in Reasoning Tasks: Although the overall gap is narrowing, top overseas models (such as OpenAI’s o3, o4-mini(high)) still maintain a nearly 10-point lead in core reasoning capabilities, particularly in mathematical reasoning and scientific reasoning tasks. This reflects that overseas models still have a deep technical moat in terms of algorithm depth, logical rigor, and complex problem-solving capabilities, which are areas that domestic models need to focus on overcoming in the future.
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Domestic Models Surpass in Specific Application Areas: The report emphasizes that domestic large models perform particularly well in agent and hallucination control tasks. For example, ByteDance’s Doubao-Seed-1.6-thinking-250715 leads the world in agent tasks with a score of 90.67, surpassing all overseas models. In hallucination control tasks, several domestic models also rank among the global leaders. This indicates that domestic models have found effective breakthroughs in combining specific application scenarios, enhancing task completion rates, and improving information accuracy.
Domestic Open-Source Models Rise, Dominating the Open-Source Ecosystem
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Domestic Open-Source Models Show Comprehensive Performance Advantages: In this evaluation, domestic open-source models such as DeepSeek-R1-0528, Qwen3 series, GLM-4.5, etc., achieved overwhelming advantages in performance. The top three spots on the open-source leaderboard are all occupied by domestic models, with the best score (66.15) nearly 20 points higher than the best score of overseas open-source models (46.37), demonstrating the strong strength and technical confidence of domestic models in the open-source field.
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Dynamic Game of Performance Gap Between Open-Source and Closed-Source Models: The report, through nearly a year of data tracking, found that the performance gap between top open-source models and closed-source models is not static. With the release of high-performance open-source models like DeepSeek-R1, the gap has significantly narrowed at times. This indicates that the power of the open-source community is reshaping the competitive landscape of large models, and high-quality open-source models can quickly close the technical distance with top closed-source models, promoting the democratization of technology across the industry.
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Small Parameter Open-Source Models Have Huge Potential: Represented by Alibaba’s Qwen3 series, several open-source models with 10B parameters or even smaller have performed impressively in evaluations, leading the leaderboard in their category. This breaks the traditional notion that “larger parameters mean better performance,” proving that through excellent model architecture and training methods, smaller models can also achieve outstanding performance in specific tasks, especially demonstrating great value in edge deployment and low-cost application scenarios.
Uneven Development of Model Capabilities, Scenario-Based Applications Become Key
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Analysis of the “Excellence Leaders” Quadrant: The SuperCLUE model quadrant chart categorizes models into four categories. Models located in the “Excellence Leaders” quadrant (such as o3, Claude Opus-4-Reasoning, Doubao-Seed-1.6-thinking-250715, etc.) perform excellently in both reasoning and application capabilities. This indicates that competition among top models is a contest of comprehensive strength, requiring both a strong technical foundation and the ability to solve problems in practical applications.
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Cost-Effectiveness and Performance Become Important Considerations: The report introduces a cost-effectiveness and overall performance distribution chart for the first time. Analysis shows that many leading domestic models provide strong capabilities while maintaining highly competitive API prices, showcasing a high cost-effectiveness advantage. In terms of overall performance (a combination of reasoning scores and reasoning speed), overseas models generally fall into the “high-performance zone,” while domestic models, although scoring well, still have significant room for improvement in reasoning speed, which directly affects user experience and the cost-effectiveness of large-scale applications.
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Maturity Index Reveals Shortcomings: The SC maturity index shows that domestic closed-source large models have reached “medium maturity” in areas such as “mathematical reasoning” and “agent tasks,” but still remain at a “low maturity” stage in “hallucination control” and “precise instruction adherence.” This clearly points out a common shortcoming in the industry, namely that models still need to strengthen their capabilities in following complex instructions and ensuring the fidelity of generated content, which is a key direction for future technological iteration and optimization.
# 02 Report Excerpt
View Report:
August Report Review
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