Technical Specifications

System Requirements

VRAM requirements for different quantization methods and context sizes

Hunyuan T1

Tencent Hunyuan T1 represents a sophisticated large-scale reasoning model, engineered for tasks demanding profound analytical and logical capabilities. Positioned as a core component within the Tencent Hunyuan model series, it is primarily designed to facilitate complex problem-solving across various domains. This model integrates a hybrid architectural paradigm to achieve its enhanced reasoning proficiency and operational efficiency.

The underlying architecture of Hunyuan T1 is characterized by a Hybrid-Transformer-Mamba Mixture of Experts (MoE) configuration. This design synergistically combines the robust contextual processing of Transformer blocks with the high speed and memory efficiency of Mamba state-space models. The MoE framework further refines computational allocation, enabling the model to dynamically activate 52 billion parameters across 16 expert networks based on input complexity. This adaptive mechanism, built upon the TurboS fast-thinking base, is specifically optimized for efficient long-sequence processing, mitigating issues such as context loss in extended textual inputs.

Operationally, Hunyuan T1 demonstrates enhanced inference capabilities and offers an accelerated decoding speed, reportedly twice as fast as comparable models under equivalent deployment conditions. Its proficiency in handling extended context lengths, up to 256,000 tokens, supports intricate long-form reasoning. The model is developed for enterprise applications requiring precise logical reasoning, scientific analysis, code generation, and advanced problem-solving, making it suitable for scenarios demanding structured logic and consistent long-form output.

No evaluation benchmarks for Hunyuan T1 available.