
What is the ERNIE X1 Turbo?
Wenxin X1 Turbo is a new generation of deep thinking and multimodal interaction model launched by Baidu in 2025. Based on Wenxin X1, it is upgraded and optimized, focusing on complex reasoning, tool invocation, long text processing, and multimodal generation, and is designed for high-level AI application scenarios. Its core advantage lies in the "think-act" closed-loop capability, which supports the model to autonomously invoke the tool chain to complete multi-step tasks, significantly improving the efficiency of problem solving.
ERNIE X1 Turbo Main Features
- Deep thinking and logical reasoning
- Supports long chain-of-thinking (Chain-of-Thought) and composite chain-of-thinking (CoT+Tool), which can disassemble complex problems into multi-step reasoning and invoke the tool chain to verify the results.
- Example: In the medical research design task, the model is automatically disassembled into four steps of "problem definition → literature search → data analysis → conclusion generation", and the code interpreter is called to complete data cleaning and visualization.
- Multimodal understanding and generation
- Fusion of multimodal data such as text, image, video, audio, etc., supports cross-modal reasoning (e.g., generating accident responsibility determination based on the CarLog screen).
- Generation capabilities: support for mixed graphic creation (e.g., generating humorous interpretations based on terrier diagrams), product diagram generation (e.g., remodeling posters into sock promotional diagrams), and video content comprehension (e.g., analyzing metaphors in movie clips).
- Tool invocation and automation
- Built-in 20+ tools (e.g. code interpreter, business data query, academic search, TreeMind tree diagram generation, etc.) to support automated task execution.
- Example: When generating a TreeMind graph of network hot terriers, the model automatically calls advanced search to get the data, and then generates a visualization chart through the code interpreter.
- Low cost and high efficiency
- The input price of $1/million tokens and the output price of $4/million tokens are onlyDeepSeek-R1of 25%, significantly reducing the cost of enterprise AI applications.
- Supports dynamic batch processing and INT8 quantized inference, with 3x faster inference and 45% lower video memory footprint.
ERNIE X1 Turbo Usage Scenario
- Enterprise Applications
- Intelligent Customer Service: Handle complex work orders (e.g., equipment failure log analysis), automatically correlate historical data to generate solutions, and increase the speed of fault location by 6 times.
- financial risk control: The timing data analysis module achieves a fraud identification accuracy of 99.21 TP4T and reduces the false alarm rate to 1.21 TP4T.
- legal document: Automatically call up case and statute libraries when generating legal documents to ensure content compliance.
- Developer Scenarios
- Code generation and debugging: Support for multimodal programming (e.g., generating code based on natural language descriptions and invoking debugging tools for optimization).
- Intelligent Body Development: Build automated tool chains (e.g., data cleansing, report generation, visualization and analysis) based on model capabilities.
- Creativity and content production
- Ad copy generation: Generate multi-style promotional copy based on product artwork and requirements with 38% accuracy improvement.
- cross-modal creativityInput "Jiangnan rain scene seven-character poem + ink painting", within 3 seconds, generate a poem that conforms to the level and oblique tone and an ink-style image with white space composition.
Difference between ERNIE X1 Turbo and ERNIE X1
dimension (math.) | ERNIE X1 | ERNIE X1 Turbo |
---|---|---|
reasoning ability | Long thought chains are supported, but require manual intervention for tool calls | Closing the "think-act" loop by autonomously invoking the tool chain |
multimodal capability | Support for basic graphic understanding | Enhanced video and audio comprehension with cross-modal reasoning support |
toolchain | Fewer built-in tools and reliance on external APIs | Integration of 20+ tools to support full process automation |
(manufacturing, production etc) costs | Input $0.002/thousand tokens, output $0.008/thousand tokens | Input $1/million tokens, output $4/million tokens (batch call is better) |
responsiveness | Typical scenario reasoning speed up by 3.2 times | Reasoning speed increased by another 3x, video memory footprint reduced by 45% |
ERNIE X1 Turbo Recommended Reasons
- technological leadership
- The world's first in-depth thinking model to call tools independently, breaking through the limitations of traditional AI "only understanding but not execution", and truly realizing "AI as an assistant".
- It outperforms DeepSeek-R1, GPT-4.5 and other models in Chinese knowledge quiz, logical reasoning and complex computation scenarios.
- cost-effectiveness
- The price is only 1%-25% of the international mainstream model, which is suitable for SMEs and individual developers to deploy AI applications at low cost.
- Supports dynamic batch processing and quantitative reasoning to further reduce reasoning costs.
- Scene Adaptability
- It covers the needs of the whole field of enterprise services, content production, scientific research and analysis, intelligent hardware, etc. It supports private deployment and meets the compliance requirements of the financial, medical and other industries.
- Developer Friendly
- Provide API interface, SDK toolkit, visualization debugging platform, support rapid integration and secondary development.
- Documentation and community resources are plentiful, lowering the technical threshold.
Wenxin Big Model X1 Turbo is a milestone product in the practicalization of AI technology, redefining the productivity boundaries of AI through deep thinking, multimodal interaction and tool invocation capabilities. Whether it is for enterprise cost reduction and efficiency, developer innovation and exploration, or personal creativity realization, X1 Turbo can provide low-cost, high-efficiency, and strongly controllable solutions, and is the currentAI macromodelOne of the preferred tools in the field.
data statistics
Relevant Navigation

The large-scale language model with powerful semantic understanding and knowledge reasoning capabilities introduced by KU Xunfei is widely used in many fields such as enterprise services, intelligent hardware, and smart government.

Nova Sonic
Amazon has introduced a new generation of generative AI speech models with unified model architecture, natural and smooth voice interaction, real-time two-way conversation capability and multi-language support, which can be widely used in multi-industry scenarios.

Tencent Hunyuan
Developed by Tencent, the Big Language Model features powerful Chinese authoring capabilities, logical reasoning in complex contexts, and reliable task execution.

EmaFusion
Ema introduces a hybrid expert modeling system that dynamically combines multiple models to accomplish enterprise-class AI tasks at low cost and high accuracy.

Endor Labs
Specializing in the field of software supply chain security management, we are committed to helping enterprises reduce the security risks of open source software dependencies through innovative technologies.

GPT-4.5
OpenAI's large-scale language model, officially launched on February 28, 2025, is an upgraded version of GPT-4.

Command A
Cohere released a lightweight AI model with powerful features such as efficient processing, long context support, multi-language and enterprise-grade security, designed for small and medium-sized businesses to achieve superior performance with low-cost hardware.

Qwen2.5-Max
The mega-scale Mixture of Experts model introduced by AliCloud's Tongyi Thousand Questions team stands out in the AI field for its excellent performance and wide range of application scenarios.
No comments...