DeepSeek Launches V3.2 Models to Challenge OpenAI and Google's AI Dominance

DeepSeek Releases New Reasoning Models to Take On ChatGPT and Gemini

Imad is a senior reporter covering Google and internet culture. Hailing from Texas, Imad started his journalism career in 2013 and has amassed bylines with The New York Times, The Washington Post, ESPN, Tom's Guide and Wired, among others. DeepSeek, the China-based AI company, has released two new reasoning-capable AI models, V3.2 and V3.2-Speciale, with the latter outperforming Gemini 3.0 Pro and GPT-5 High in benchmarks, the company said in news release on Monday. At the moment, V3.2 is available on the app and web, whereas V3.2-Speciale can only be accessed via the API. DeepSeek V3.2 is a follow-up to V3.2-Exp, which stands for experimental and was released in September. The Hangzhou-based AI company says V3.2 surpasses the performance of OpenAI's GPT-5 in reasoning benchmarks and has reasoning performance "on par" with Gemini 3.0 Pro. DeepSeek didn't release testing against GPT-5 Pro. That could be because ChatGPT is blocked in China. What's more, DeepSeek said it's committed to staying open source, meaning any company can load DeepSeek's models for free. But considering V3.2 has 685 billion parameters, it can only run on a giant server stack with millions of dollars in hardware. Don't miss any of our unbiased tech content and lab-based reviews. Add CNET as a preferred Google source. DeepSeek didn't immediately respond to a request for comment. DeepSeek's release of 3.2 comes as the company continues to put American AI companies on notice. The company first gained worldwide attention earlier this year when it released a reasoning-capable model online, for free. It immediately turned the narrative about reasoning models on its head, showing that it's possible to run smarter, more capable AI models at a fraction of the cost. This spooked Wall Street, with some wondering if OpenAI, Google and Anthropic weren't innovating fast enough. Since then, ChatGPT, Gemini and Claude have all released reasoning-level models for free, with higher-level "thinking" models being available for paid subscribers. DeepSeek-V3.2-Speciale won gold in the 2025 International Mathematical Olympiad (IMO) and International Olympiad in Informatics (IOI), the company said. (Disclosure: Ziff Davis, CNET's parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.)

DeepSeek just dropped two insanely powerful AI models that rival GPT-5 and they're totally free

Chinese artificial intelligence startup DeepSeek released two powerful new AI models on Sunday that the company claims match or exceed the capabilities of OpenAI's GPT-5 and Google's Gemini-3.0-Pro -- a development that could reshape the competitive landscape between American tech giants and their Chinese challengers. The Hangzhou-based company launched DeepSeek-V3.2, designed as an everyday reasoning assistant, alongside DeepSeek-V3.2-Speciale, a high-powered variant that achieved gold-medal performance in four elite international competitions: the 2025 International Mathematical Olympiad, the International Olympiad in Informatics, the ICPC World Finals, and the China Mathematical Olympiad. The release carries profound implications for American technology leadership. DeepSeek has once again demonstrated that it can produce frontier AI systems despite U.S. export controls that restrict China's access to advanced Nvidia chips -- and it has done so while making its models freely available under an open-source MIT license. "People thought DeepSeek gave a one-time breakthrough but we came back much bigger," wrote Chen Fang, who identified himself as a contributor to the project, on X (formerly Twitter). The release drew swift reactions online, with one user declaring: "Rest in peace, ChatGPT." How DeepSeek's sparse attention breakthrough slashes computing costs At the heart of the new release lies DeepSeek Sparse Attention, or DSA -- a novel architectural innovation that dramatically reduces the computational burden of running AI models on long documents and complex tasks. Traditional AI attention mechanisms, the core technology allowing language models to understand context, scale poorly as input length increases. Processing a document twice as long typically requires four times the computation. DeepSeek's approach breaks this constraint using what the company calls a "lightning indexer" that identifies only the most relevant portions of context for each query, ignoring the rest. According to DeepSeek's technical report, DSA reduces inference costs by roughly half compared to previous models when processing long sequences. The architecture "substantially reduces computational complexity while preserving model performance," the report states. Processing 128,000 tokens -- roughly equivalent to a 300-page book -- now costs approximately $0.70 per million tokens for decoding, compared to $2.40 for the previous V3.1-Terminus model. That represents a 70% reduction in inference costs. The 685-billion-parameter models support context windows of 128,000 tokens, making them suitable for analyzing lengthy documents, codebases, and research papers. DeepSeek's technical report notes that independent evaluations on long-context benchmarks show V3.2 performing on par with or better than its predecessor "despite incorporating a sparse attention mechanism." The benchmark results that put DeepSeek in the same league as GPT-5 DeepSeek's claims of parity with America's leading AI systems rest on extensive testing across mathematics, coding, and reasoning tasks -- and the numbers are striking. On AIME 2025, a prestigious American mathematics competition, DeepSeek-V3.2-Speciale achieved a 96.0% pass rate, compared to 94.6% for GPT-5-High and 95.0% for Gemini-3.0-Pro. On the Harvard-MIT Mathematics Tournament, the Speciale variant scored 99.2%, surpassing Gemini's 97.5%. The standard V3.2 model, optimized for everyday use, scored 93.1% on AIME and 92.5% on HMMT -- marginally below frontier models but achieved with substantially fewer computational resources. Most striking are the competition results. DeepSeek-V3.2-Speciale scored 35 out of 42 points on the 2025 International Mathematical Olympiad, earning gold-medal status. At the International Olympiad in Informatics, it scored 492 out of 600 points -- also gold, ranking 10th overall. The model solved 10 of 12 problems at the ICPC World Finals, placing second. These results came without internet access or tools during testing. DeepSeek's report states that "testing strictly adheres to the contest's time and attempt limits." On coding benchmarks, DeepSeek-V3.2 resolved 73.1% of real-world software bugs on SWE-Verified, competitive with GPT-5-High at 74.9%. On Terminal Bench 2.0, measuring complex coding workflows, DeepSeek scored 46.4% -- well above GPT-5-High's 35.2%. The company acknowledges limitations. "Token efficiency remains a challenge," the technical report states, noting that DeepSeek "typically requires longer generation trajectories" to match Gemini-3.0-Pro's output quality. Why teaching AI to think while using tools changes everything Beyond raw reasoning, DeepSeek-V3.2 introduces "thinking in tool-use" -- the ability to reason through problems while simultaneously executing code, searching the web, and manipulating files. Previous AI models faced a frustrating limitation: each time they called an external tool, they lost their train of thought and had to restart reasoning from scratch. DeepSeek's architecture preserves the reasoning trace across multiple tool calls, enabling fluid multi-step problem solving. To train this capability, the company built a massive synthetic data pipeline generating over 1,800 distinct task environments and 85,000 complex instructions. These included challenges like multi-day trip planning with budget constraints, software bug fixes across eight programming languages, and web-based research requiring dozens of searches. The technical report describes one example: planning a three-day trip from Hangzhou with constraints on hotel prices, restaurant ratings, and attraction costs that vary based on accommodation choices. Such tasks are "hard to solve but easy to verify," making them ideal for training AI agents. DeepSeek employed real-world tools during training -- actual web search APIs, coding environments, and Jupyter notebooks -- while generating synthetic prompts to ensure diversity. The result is a model that generalizes to unseen tools and environments, a critical capability for real-world deployment. DeepSeek's open-source gambit could upend the AI industry's business model Unlike OpenAI and Anthropic, which guard their most powerful models as proprietary assets, DeepSeek has released both V3.2 and V3.2-Speciale under the MIT license -- one of the most permissive open-source frameworks available. Any developer, researcher, or company can download, modify, and deploy the 685-billion-parameter models without restriction. Full model weights, training code, and documentation are available on Hugging Face, the leading platform for AI model sharing. The strategic implications are significant. By making frontier-capable models freely available, DeepSeek undermines competitors charging premium API prices. The Hugging Face model card notes that DeepSeek has provided Python scripts and test cases "demonstrating how to encode messages in OpenAI-compatible format" -- making migration from competing services straightforward. For enterprise customers, the value proposition is compelling: frontier performance at dramatically lower cost, with deployment flexibility. But data residency concerns and regulatory uncertainty may limit adoption in sensitive applications -- particularly given DeepSeek's Chinese origins. Regulatory walls are rising against DeepSeek in Europe and America DeepSeek's global expansion faces mounting resistance. In June, Berlin's data protection commissioner Meike Kamp declared that DeepSeek's transfer of German user data to China is "unlawful" under EU rules, asking Apple and Google to consider blocking the app. The German authority expressed concern that "Chinese authorities have extensive access rights to personal data within the sphere of influence of Chinese companies." Italy ordered DeepSeek to block its app in February. U.S. lawmakers have moved to ban the service from government devices, citing national security concerns. Questions also persist about U.S. export controls designed to limit China's AI capabilities. In August, DeepSeek hinted that China would soon have "next generation" domestically built chips to support its models. The company indicated its systems work with Chinese-made chips from Huawei and Cambricon without additional setup. DeepSeek's original V3 model was reportedly trained on roughly 2,000 older Nvidia H800 chips -- hardware since restricted for China export. The company has not disclosed what powered V3.2 training, but its continued advancement suggests export controls alone cannot halt Chinese AI progress. What DeepSeek's release means for the future of AI competition The release arrives at a pivotal moment. After years of massive investment, some analysts question whether an AI bubble is forming. DeepSeek's ability to match American frontier models at a fraction of the cost challenges assumptions that AI leadership requires enormous capital expenditure. The company's technical report reveals that post-training investment now exceeds 10% of pre-training costs -- a substantial allocation credited for reasoning improvements. But DeepSeek acknowledges gaps: "The breadth of world knowledge in DeepSeek-V3.2 still lags behind leading proprietary models," the report states. The company plans to address this by scaling pre-training compute. DeepSeek-V3.2-Speciale remains available through a temporary API until December 15, when its capabilities will merge into the standard release. The Speciale variant is designed exclusively for deep reasoning and does not support tool calling -- a limitation the standard model addresses. For now, the AI race between the United States and China has entered a new phase. DeepSeek's release demonstrates that open-source models can achieve frontier performance, that efficiency innovations can slash costs dramatically, and that the most powerful AI systems may soon be freely available to anyone with an internet connection. As one commenter on X observed: "Deepseek just casually breaking those historic benchmarks set by Gemini is bonkers." The question is no longer whether Chinese AI can compete with Silicon Valley. It's whether American companies can maintain their lead when their Chinese rival gives comparable technology away for free.

DeepSeek Releases New Reasoning Models to Match GPT-5, Rival Gemini 3 Pro | AIM

Both models and the accompanying technical report have been released as open source on Hugging Face. Chinese AI lab DeepSeek has launched two new reasoning-first AI models, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, expanding its suite of systems for agents, tool-use and complex inference. Both the models and the accompanying technical report have been released as open source on Hugging Face. The company announced on X that V3.2 is the official successor to V3.2-Exp and is now available across its app, web interface and API. The Speciale variant is offered only through a temporary API endpoint until December 15, 2025. DeepSeek said V3.2 aims to balance inference efficiency with long-context performance, calling it "your daily driver at GPT-5 level performance." The V3.2-Speciale model, positioned for high-end reasoning tasks, "rivals Gemini-3.0-Pro," the company said. According to DeepSeek, Speciale delivers gold-level (expert human proficiency) results across competitive benchmarks such as the IMO, CMO and ICPC World Finals. The models introduce an expansion of DeepSeek's agent-training approach, supported by a new synthetic dataset spanning more than 1,800 environments and 85,000 complex instructions. The company stated that V3.2 is its first model to integrate thinking directly into tool use, allowing structured reasoning to operate both within and alongside external tools. Alongside the release, DeepSeek updated its API, noting that V3.2 maintains the same usage pattern as its predecessor. The Speciale model is priced the same as V3.2 but does not support tool calls. The company also highlighted a new capability in V3.2 described as "Thinking in Tool-Use," with additional details provided in its developer documentation. The company recently also released a new open-weight model, DeepSeekMath-V2. The model, as per the AI lab, demonstrates strong theorem-proving capabilities in mathematics and achieved gold-level scores on the International Mathematics Olympiad (IMO) 2025.

DeepSeek's New AI Model Achieves Gold-Level Results, Rivals GPT-5 and Gemini 3 Pro

The DeepSeek V3.2-Speciale model delivers gold-level results in IMO, CMO, ICPC, and IOI 2025. China's frontier AI lab, DeepSeek has released its new reasoning AI models that rival the performance of OpenAI's GPT-5 High and Google's Gemini 3 Pro. There are two AI models including DeepSeek-V3.2 and DeepSeek-V3.2-Speciale. The DeepSeek-V3.2 model is the successor to the V3.2-Experimental model and it powers the DeepSeek app. The more powerful, DeepSeek-V3.2-Speciale is quite performant and it's only available via the API. This special model achieves gold-level results in IMO, CMO, ICPC World Finals, and IOI 2025, something that OpenAI and Google have achieved with their specialized models. A variant of Gemini 2.5 Deep Think achieved the Gold medal at IMO 2025. While it's far more capable, it also consumes much more token and there is no tool support for this model yet. In terms of agentic capabilities too, the new models are much better. Now, coming to benchmarks, the DeepSeek-V3.2-Speciale model achieves 96.0 in AIME 2025 whereas GPT-5 High gets 94.6 and Gemini 3 Pro stands at 95.0. In Humanity's Last Exam (HLE), the new special model gets 30.6 whereas Gemini 3 Pro achieves 37.7. Now, in SWE Verified, DeepSeek's new model achieves 73.1, a bit lower than Gemini 3 Pro (76.2). All in all, the new model by DeepSeek is quite frontier-class and it highlights that China is a strong contender in the AI race. Along with Alibaba's Qwen 3 AI models, now DeepSeek is delivering strong performance across various benchmarks.

DeepSeek launches pair of AI models to challenge OpenAI, Google

China-based DeepSeek (DEEPSEEK) has launched a pair of new artificial intelligence models, DeepSeek-V3.2 and DeepSeek-V3.2-Speciale, which are open-sourced and topped or matched the results of OpenAI's (OPENAI) GPT-5 and Google's (GOOG)(GOOGL) Gemini 3 Pro in some benchmarks. DeepSeek-V3.2 is now DeepSeek-V3.2 and V3.2-Speciale matched or outperformed GPT-5 and Gemini 3 Pro in some benchmarks, notably in mathematical and informatics Olympiad tasks. DeepSeek introduced DSA for efficient long-sequence attention, a scalable RL framework, and a large-scale agentic task synthesis pipeline. DeepSeek cites inefficient vanilla attention mechanisms, lack of post-training compute investment, and lagging generalization and instruction-following abilities.