Core Insights - DeepSeek has released two official model versions: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, with the former available on the official website, app, and API, while the latter is currently accessible only as a temporary API for community evaluation [1][3]. Model Performance - DeepSeek-V3.2 aims to balance reasoning capability and output length, making it suitable for daily use. In benchmark tests, it achieved performance comparable to GPT-5 and slightly below Gemini-3.0-Pro, with a significant reduction in output length compared to Kimi-K2-Thinking, leading to lower computational costs and reduced user wait times [3][4]. - DeepSeek-V3.2-Speciale is designed to push the limits of reasoning capabilities, serving as an enhanced version of DeepSeek-V3.2, and incorporates theorem-proving abilities from DeepSeek-Math-V2. It performed comparably to Gemini-3.0-Pro in mainstream reasoning benchmarks and won gold medals in several prestigious competitions, including IMO 2025 and ICPC World Finals 2025, achieving second and tenth place among human competitors, respectively [3][4]. Benchmark Comparisons - In various benchmark tests, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale demonstrated competitive performance: - AIME 2025: DeepSeek-V3.2 scored 93.1, while DeepSeek-V3.2-Speciale scored 96.0 [4]. - HMMT Feb 2025: DeepSeek-V3.2 scored 92.5, and DeepSeek-V3.2-Speciale scored 99.2 [4]. - IMOAnswerBench: DeepSeek-V3.2 scored 78.3, and DeepSeek-V3.2-Speciale scored 84.5 [4]. - CodeForces: DeepSeek-V3.2 scored 2386, while DeepSeek-V3.2-Speciale scored 2701 [4]. Cost Efficiency - The introduction of DeepSeek-V3.2-Exp, based on V3.1-Terminus with a new attention mechanism (DSA), has led to significant improvements in training and reasoning efficiency, resulting in a notable reduction in model costs. This cost reduction enhances the model's cost-effectiveness and potential for broader application [4].

Core Insights - DeepSeek has released two official model versions: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, aimed at enhancing reasoning capabilities and output length for various applications [1][4] Model Performance - DeepSeek-V3.2 achieved performance comparable to GPT-5 in public reasoning benchmarks, slightly below Gemini-3.0-Pro, while significantly reducing output length compared to Kimi-K2-Thinking, thus lowering computational costs and user wait times [1][3] - The DeepSeek-V3.2-Speciale model demonstrated exceptional instruction-following, rigorous mathematical proof, and logical validation capabilities, achieving gold medal-level results in major competitions such as IMO 2025 and ICPC World Finals 2025 [2] Benchmark Comparisons - In various benchmark tests, DeepSeek-V3.2-Speciale outperformed the standard version in complex tasks, although it required significantly more tokens, indicating higher costs [3] - Specific benchmark scores include: - AIME 2025: DeepSeek-V3.2-Speciale scored 96.0, while DeepSeek-V3.2 scored 93.1 [3] - HMMT Feb 2025: DeepSeek-V3.2-Speciale scored 99.2, compared to DeepSeek-V3.2's 92.5 [3] - IMOAnswerBench: DeepSeek-V3.2-Speciale scored 84.5, while DeepSeek-V3.2 scored 78.3 [3] Model Features - DeepSeek-V3.2 is the first model to integrate reasoning with tool usage, supporting both reasoning and non-reasoning modes for tool calls, enhancing its versatility [4] - The model has improved generalization capabilities through a large-scale agent training data synthesis method, allowing it to perform well in real-world applications [4]

Core Insights - DeepSeek has launched two new models, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, marking a significant advancement in AI capabilities, particularly in reasoning and output efficiency [2][3] - The V3.2 model is positioned as the strongest open-source large model, outperforming competitors in various benchmarks while significantly reducing output length and computational costs [3][4] - The V3.2 model integrates a new sparse attention mechanism (DSA) to enhance performance in long-context scenarios, while also improving the model's ability to follow instructions and generalize in complex environments [8][9] Model Performance - In benchmark tests, DeepSeek-V3.2 achieved competitive scores against models like GPT-5, Claude 4.5, and Gemini 3 Pro, with notable strengths in specific areas [4][5] - The V3.2 model demonstrated superior performance in question-and-answer scenarios, providing detailed and accurate travel recommendations through advanced tool usage [5][6] - The V3.2 Speciale model focuses on maximizing reasoning capabilities, achieving results comparable to Gemini 3.0 Pro in mainstream reasoning benchmarks, although it requires a higher token cost and is not designed for everyday use [9][10] Development Focus - DeepSeek emphasizes practical usability and generalization in its models, aiming to overcome common pitfalls in AI interactions, such as making basic common-sense errors [6][8] - The company is committed to enhancing the reasoning abilities of its models, as evidenced by the integration of advanced mathematical reasoning capabilities from the recently released DeepSeek-Math-V2 [9][10] - The competitive landscape for large models is intensifying, with major players like GPT-5 and Gemini 3 pushing the boundaries of AI capabilities, suggesting a dynamic future for AI development [10]

Core Insights - DeepSeek announced the release of two official model versions: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale [1] Model Overview - DeepSeek-V3.2 aims to balance reasoning capability and output length, making it suitable for everyday use, such as Q&A scenarios and general agent tasks [1] - In benchmark tests for reasoning, DeepSeek-V3.2 achieved performance comparable to GPT-5, slightly below Gemini-3.0-Pro [1] - Compared to Kimi-K2-Thinking, V3.2 significantly reduced output length, leading to lower computational costs and reduced user wait times [1] Special Features - DeepSeek-V3.2-Speciale is designed to push the reasoning capabilities of open-source models to the limit, exploring the boundaries of model performance [1] - This version is an enhanced long-thinking variant of DeepSeek-V3.2, incorporating theorem-proving capabilities from DeepSeek-Math-V2 [1] - The model exhibits excellent instruction-following, rigorous mathematical proof, and logical verification abilities, performing comparably to Gemini-3.0-Pro in mainstream reasoning benchmark tests [1]

Core Insights - DeepSeek has released two new models: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, aimed at enhancing reasoning capabilities and output length for various applications [1][2]. Model Performance - DeepSeek-V3.2 achieved performance comparable to GPT-5 and slightly below Gemini-3.0-Pro in public reasoning benchmarks, while significantly reducing output length compared to Kimi-K2-Thinking, thus lowering computational costs and user wait times [1][3]. - The DeepSeek-V3.2-Speciale model demonstrated exceptional instruction-following, rigorous mathematical proof, and logical validation capabilities, achieving gold medal-level performance in major competitions such as IMO 2025 and ICPC World Finals 2025 [2][3]. Benchmark Comparisons - In various benchmark tests, DeepSeek-V3.2-Speciale outperformed standard versions and other models, with notable scores in AIME 2025 (96.0) and HMMT Feb 2025 (99.2), while also achieving high rankings in IMOAnswerBench and LiveCodeBench [3]. - The performance of DeepSeek-V3.2-Speciale in complex tasks was significantly better than the standard version, although it required more tokens, indicating higher operational costs [3]. Model Features - DeepSeek-V3.2 is the first model to integrate reasoning with tool usage, supporting both reasoning and non-reasoning modes for tool invocation, enhancing its versatility [4]. - The model has improved generalization capabilities through a novel large-scale agent training data synthesis method, allowing it to perform well in real-world applications [4].

Core Insights - DeepSeek has officially released two models: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, with updates available on the official website, app, and API [1] - DeepSeek-V3.2 aims to balance reasoning capabilities and output length, making it suitable for everyday use cases such as Q&A and general agent tasks [1] - DeepSeek-V3.2-Speciale is designed to push the reasoning capabilities of open-source models to the limit, enhancing long-thinking abilities and incorporating theorem-proving capabilities from DeepSeek-Math-V2 [1] Model Performance - The V3.2-Speciale model exhibits excellent instruction-following, rigorous mathematical proof, and logical verification capabilities, performing comparably to leading international models on mainstream reasoning benchmarks [1] - Notably, the V3.2-Speciale model has achieved gold medals in several prestigious competitions, including IMO 2025, CMO 2025, ICPC World Finals 2025, and IOI 2025 [1] - In the ICPC and IOI competitions, the model's performance reached the level of the second and tenth place among human competitors, respectively [1]

Core Insights - DeepSeek has launched two new models: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, aiming to enhance reasoning capabilities and output length for various applications [1][2][3] Model Features - DeepSeek-V3.2 is designed for everyday use, balancing reasoning ability and output length, and has achieved performance comparable to GPT-5 in benchmark tests [2][3] - DeepSeek-V3.2-Speciale enhances long reasoning capabilities and incorporates theorem proving abilities from DeepSeek-Math-V2, excelling in complex tasks but requiring more tokens and higher costs [3][4] Technological Advancements - DeepSeek-V3.2 is the first model to integrate reasoning with tool usage, supporting both reasoning and non-reasoning modes for tool invocation, significantly improving generalization capabilities [4] - The model has been trained on over 1,800 environments and 85,000 complex instructions, narrowing the performance gap between open-source and closed-source models [4] Market Outlook - The AI industry is experiencing a resonance period, with rapid expansion in AI infrastructure and commercialization of downstream applications, expected to continue thriving through 2026 [5][6][7] - Investment opportunities are identified in domestic AI chains, overseas AI hardware markets, and innovative applications in the domestic edge AI industry [7]

Core Insights - DeepSeek has launched two new models, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, which are leading in reasoning capabilities globally [1][3]. Model Overview - DeepSeek-V3.2 aims to balance reasoning ability and output length, suitable for everyday use such as Q&A and general intelligence tasks. It has reached the level of GPT-5 in public reasoning tests, slightly below Google's Gemini3 Pro [3]. - DeepSeek-V3.2-Speciale is designed to push the reasoning capabilities of open-source models to the extreme, combining features from DeepSeek-Math-V2 for theorem proving, and excels in instruction following and logical verification [3][4]. Performance Metrics - Speciale has surpassed Google's Gemini3 Pro in several reasoning benchmark tests, including the American Mathematics Invitational, Harvard MIT Mathematics Competition, and International Mathematical Olympiad [4]. - In various benchmarks, DeepSeek's performance is competitive, with specific scores noted in a comparative table against GPT-5 and Gemini-3.0 [5]. Technical Limitations - Despite achievements, DeepSeek acknowledges limitations compared to proprietary models like Gemini3 Pro, particularly in knowledge breadth and token efficiency [6]. - The company plans to enhance pre-training computation and optimize reasoning chains to improve model efficiency and capabilities [6][7]. Mechanism Innovations - DeepSeek introduced a Sparse Attention Mechanism (DSA) to reduce computational complexity, which has proven effective in enhancing performance without sacrificing long-context capabilities [7][8]. - Both new models incorporate this mechanism, making DeepSeek-V3.2 a cost-effective alternative that narrows the performance gap with proprietary models [8]. Community Reception - The release has been positively received in the community, with users noting that DeepSeek's models are now comparable to GPT-5 and Gemini3 Pro, marking a significant achievement in open-source model development [8].

Group 1 - DeepSeek V3.2 has been officially released, enhancing Agent capabilities and integrating reasoning and thinking [1] - Doubao Mobile Assistant has released a technical preview version [1] - Tsinghua University has established a research institute for embodied intelligence and robotics [1] Group 2 - Didi's autonomous driving service is undergoing trial operations in Guangzhou, offering all-weather, fully unmanned Robotaxi services [2] - HSBC has formed a strategic partnership with Mistral AI to enhance the application of generative AI in banking operations [2]

Core Insights - DeepSeek has officially released two models: DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, following the experimental version launched two months ago [1] - DeepSeek-V3.2 aims to balance reasoning capability and output length, making it suitable for everyday use, such as Q&A scenarios and general agent tasks [1] - The performance of DeepSeek-V3.2 in benchmark tests is comparable to GPT-5 and slightly lower than Gemini-3.0-Pro, with significantly reduced output length compared to Kimi-K2-Thinking, leading to lower computational costs and reduced user wait times [1] Model Specifications - DeepSeek-V3.2-Speciale is designed to push the reasoning capabilities of open-source models to the limit, serving as an enhanced version of DeepSeek-V3.2 with theorem-proving abilities from DeepSeek-Math-V2 [2] - This model excels in instruction following, rigorous mathematical proofs, and logical validation, achieving performance on par with Gemini-3.0-Pro in mainstream reasoning benchmarks [2] - DeepSeek-V3.2-Speciale has won gold medals in prestigious competitions such as IMO 2025, CMO 2025, ICPC World Finals 2025, and IOI 2025, with ICPC and IOI scores reaching the second and tenth positions among human competitors, respectively [2] - While the Speciale model significantly outperforms the standard version in complex tasks, it consumes more tokens and incurs higher costs [2] - Currently, DeepSeek-V3.2-Speciale is available only for research purposes and does not support tool invocation, nor has it been optimized for everyday conversation and writing tasks [2]