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Tencent HY 2.0 is officially unveiled: MoE architecture upgrade, Think and Instruct dual versions released

Tencent HY 2.0 is officially unveiled: MoE architecture upgrade, Think and Instruct dual versions released

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The Tencent Hunyuan team announced the official release of the latest version of the language model, Tencent HY 2.0, which is open to developers and enterprises through Tencent Cloud API. This upgrade adopts a hybrid expert (MoE) architecture with a total parameter scale of 406 billion, activation parameters of 32 billion, and supports a maximum of 256K context windows, which is significantly improved in mathematical reasoning, code generation, and complex task execution compared to the previous generation model. According to the official introduction, HY 2.0 scored 73.4 points on IMO-AnswerBench, and its score on agent tasks such as SWE-bench Verified and Tau2-Bench also jumped significantly.

HY 2.0 provides two types of optimized versions: Tencent HY 2.0 Think is aimed at deep reasoning, code generation, and complex instruction scenarios, and the cloud interface currently supports a maximum input of 128K and output of 64K, focusing more on long texts, multi-round dialogues, and difficult reasoning capabilities; Tencent HY 2.0 Instruct is aimed at daily conversations, creation, and high-concurrency services, with a maximum input of 128K and an output of 16K, emphasizing responsiveness and universal stability. In terms of training strategy, the official emphasizes the introduction of RLVR + RLHF dual-stage reinforcement learning, and balances "thinking depth" and generation efficiency through length penalty and task sandbox design.

At present, HY 2.0 has been connected to its own applications such as Tencent Yuanbao, and provides API calls and enterprise access capabilities on Tencent Cloud. The specific price, current limiting strategy and more technical details are still subject to Tencent Cloud's official documentation, and the original data of some internal benchmarks has not yet been fully disclosed, and the external performance comparison is mainly based on the indicators and instructions released by Tencent.

FAQ

Q: What is Tencent HY 2.0?

A: It is the latest generation of Tencent Hunyuan's general-purpose large language model, using MoE architecture, with total parameters of 406B and activation of 32B, focusing on reasoning, code and long text capabilities.

Q: What are the specific versions of this release?

A: There are two main types of text models: Tencent HY 2.0 Think (for deep reasoning) and Tencent HY 2.0 Instruct (for general dialogue and authoring).

Q: What are the context length and input/output specifications of HY 2.0?

A: The family model claims to support up to 256K context, and the current maximum input of the cloud Think/Instruct interface is 128K, of which the maximum output of Think is 64K and the maximum output of Instruct is 16K.

Q: What is the main difference between Think and Instruct?

A: Think is more suitable for "slow thinking" tasks such as complex reasoning, code generation, and agent tool calls. Instruct is better suited for chat, writing, and business Q&A scenarios with high concurrency and high response requirements.

Q: Is it completely open source, how to access and use it?

A: HY 2.0 currently provides commercial services in the form of Tencent Cloud API, and has been implemented in some Tencent products.

Tencent Hunyuan HY2.0 large language model Tencent HY2 point 0MoE hybrid expert architecture Tencent HY2 points 0 supports 256K long context Tencent HY2 points 0 mathematical reasoning ability has been improved How effective is Tencent HY2 point 0 code generation? Tencent HY2 points 0 complex task execution performance Tencent HY2 points 0 IMOAnswerBench score Tencent HY2.0 performance in the SWEbench benchmark TencentHY2 points 0 in the Tau2Bench agent Tencent HY2 point 0Think deep reasoning version Tencent HY2 point 0 Instruct general dialog version What usage scenarios is HY2 point 0Think suitable for? HY2 point 0 Instruct is suitable for high-concurrency services HY2 point 0 longest 256K context window introduction HY2 point 0 cloud interface input and output specifications HY2 points 0, total parameters 406 billion, activated 32 billion How to improve long-form writing with HY2 points 0 Hunyuan HY2 points 0 multi-round dialogue experience evaluation Application of HY2 point 0 in code-assisted development HY2 point 0 performance in agent tool calls HY2.0 used RLVR plus RLHF for reinforcement learning HY2 point 0 How to balance depth of thinking and efficiency HY2 point 0 mission sandbox and length penalty design Tencent Yuanbao has been connected to the Hunyuan HY2.0 model Tencent Cloud HY2.0 API call access process How enterprises can build industry assistants based on HY2 point 0 The application of HY2 point 0 in the Q&A of the enterprise knowledge base HY2 point 0 landing case in the customer service robot scenario Does HY2 point 0 support legal compliance review of long documents? HY2 points 0 advantages in education and learning counseling scenarios HY2 points 0 in data analysis and report generation capabilities HY2.0 performance comparison with the previous generation of hybrid model HY2 points 0 horizontal evaluation with other mainstream large models HY2 points 0 multilingual support and localization capabilities HY2 points 0 in game planning and plot creation applications HY2 points 0 to the ecological value of mini programs and enterprise WeChat HY2 point 0 performance in audio and video copy generation HY2 point 0 is suitable for individual developers HY2:0 call price and billing method reference HY2.0 current restriction policy affects large-scale business HY2 point 0 What quotas do you need to pay attention to when accessing the API? HY2 points 0 is suitable for building a personal intelligent knowledge assistant HY2 point 0 plug-in scheme in tool-based applications HY2 point 0 is combined with vector database for retrieval enhancement HY2 point 0 is the value of automated processes within the company HY2 points 0 help enterprises upgrade their search and recommendation systems HY2.0 potential in government and public service scenarios HY2 points 0 in the application of financial risk control compliance text analysis HY2 point 0 will open model weight download in the future HY2.0 ecological development route and community resource attention

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