Technical Specifications of hunyuan-turbos-longtext-128k-20250325
| Specification | Details |
|---|---|
| Model ID | hunyuan-turbos-longtext-128k-20250325 |
| Provider | Tencent Hunyuan |
| Model family | Hunyuan-TurboS / long-context text generation model variant |
| Context window | 128K tokens |
| Primary modality | Text |
| Architecture background | Hunyuan-TurboS is described by Tencent as a hybrid Transformer-Mamba MoE model family with adaptive long/short reasoning behavior. This appears to be the technical foundation behind the TurboS line, and the longtext variant is best understood as a long-context API deployment of that family. |
| Positioning | Optimized for long-document understanding, writing, knowledge tasks, and instruction-following workloads that benefit from extended context. This is an inference based on the 128K context positioning and Tencent’s description of TurboS improvements in text understanding, writing, QA, and bilingual/general performance. |
| Availability | Accessible on CometAPI under the model ID hunyuan-turbos-longtext-128k-20250325. |
What is hunyuan-turbos-longtext-128k-20250325?
hunyuan-turbos-longtext-128k-20250325 is CometAPI’s platform identifier for a Tencent Hunyuan TurboS long-context language model endpoint built for text generation and long-input processing. Based on publicly available Tencent Hunyuan and Hunyuan-TurboS materials, the model belongs to Tencent’s broader Hunyuan LLM ecosystem, which focuses on strong instruction following, text understanding, knowledge tasks, and efficient reasoning.
The “longtext-128k” naming strongly indicates a 128K-token long-context deployment intended for workloads such as summarizing long reports, analyzing large documents, handling extended conversations, and generating content from substantial source material. That interpretation aligns with Tencent’s published 128K context positioning for its text models and with the TurboS family’s emphasis on long-sequence efficiency.
Tencent’s technical report for Hunyuan-TurboS describes the family as combining Transformer contextual understanding with Mamba-based long-sequence efficiency in a mixture-of-experts architecture, alongside an adaptive long-short chain-of-thought mechanism. While that paper discusses the TurboS family rather than this exact CometAPI SKU, it provides the clearest public technical context for what this model line is designed to do.
Main features of hunyuan-turbos-longtext-128k-20250325
- 128K long-context processing: The model is positioned for large-input tasks, making it suitable for lengthy documents, multi-section prompts, retrieval-augmented workflows, and extended dialogue state.
- TurboS family performance focus: Tencent describes Hunyuan-TurboS as a flagship model line with stronger thinking ability and improved user experience, including gains in math, logic, code, text creation, text understanding, knowledge Q&A, and general Chinese/English usage.
- Hybrid long-sequence architecture: Public Hunyuan-TurboS research describes a hybrid Transformer-Mamba MoE design intended to improve long-sequence training and inference efficiency while preserving strong contextual modeling.
- Adaptive reasoning behavior: Tencent’s TurboS research says the model family can dynamically shift between shorter and deeper reasoning modes depending on task complexity, which helps balance speed and analytical depth.
- Instruction-following and writing utility: Tencent’s Hunyuan model materials highlight strong instruction following, multi-turn interaction, long-text understanding, and writing capability, which are especially relevant for assistants, enterprise knowledge tools, and document workflows.
- CometAPI-ready deployment: The model is exposed on CometAPI as a directly callable API model, allowing developers to integrate it into applications without separately managing Tencent-native infrastructure.
How to access and integrate hunyuan-turbos-longtext-128k-20250325
Step 1: Sign Up for API Key
Sign up on CometAPI and create an API key from your dashboard. Once you have the key, store it securely and use it as your bearer token for all API requests to hunyuan-turbos-longtext-128k-20250325.
Step 2: Send Requests to hunyuan-turbos-longtext-128k-20250325 API
Use the OpenAI-compatible CometAPI interface and set the model field to hunyuan-turbos-longtext-128k-20250325.
curl https://api.cometapi.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $COMETAPI_API_KEY" \
-d '{
"model": "hunyuan-turbos-longtext-128k-20250325",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Summarize the following long document and list the key decisions."
}
]
}'
Step 3: Retrieve and Verify Results
Read the generated content from the API response, then verify output quality for your use case—especially on long-document summarization, extraction, or reasoning tasks. For production use, it is good practice to validate formatting, factual consistency, and completeness against your source inputs before downstream automation.