GPT-4 1106 Preview
Unleash the prowess of advanced dialogue simulations and elevate your AI response quality.
GPT-4 1106 Preview, developed by OpenAI, is a powerful language model. With a large context window, it excels in simulated dialogues and multi-turn conversations, making it versatile across various digital communication platforms.
| License | openai |
|---|---|
| Context window(in thousands) | 128000 |
Use cases for GPT-4 1106 Preview
- High-context conversational AI: GPT-4 1106 Preview is ideal for building chatbots that can handle long and complex conversations, offering a more natural interaction for users.
- Advanced text generation: Given the high MT Bench score, this model is perfect for creating high-quality content such as articles, stories, and marketing copy.
- Complex task handling: With a high MMLU score, it excels in tasks that require understanding complex instructions and providing detailed responses, like coding assistance and academic research support.
| Arena Elo | 1251 |
|---|---|
| MMLU | N/A |
| MT Bench | 9.32 |
GPT-4 1106 Preview delivers top-tier performance in human response quality, translation benchmarks, and knowledge reasoning scores.
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| Throughput(output tokens per second) | 19 |
|---|---|
| Latency(seconds to first tokens chunk received) | 0.59 |
| Total Response Time(seconds to output 100 tokens) | 6.1 |
This model offers moderate throughput, high latency, and slower total response time. It's not ideal for real-time applications needing instant responses but works well for tasks where speed is less critical.
The cost per 1,000 tokens for running the model with Telnyx Inference is $0.0010. For instance, analyzing 1,000,000 customer chats, assuming each chat is 1,000 tokens long, would cost $1,000.
What's Twitter saying?
- GPT-4 Model Performance Comparison: Thomas Ahle shares benchmark results, noting that GPT-4-0613 outperforms GPT-4-1106-preview in some projects. (Source: @thomasahle)
- Latency Issues with GPT-4-Turbo on Azure OpenAI: Adrian Hills discusses significant latency issues with GPT-4-Turbo (1106-Preview) on Azure OpenAI, highlighting it is slower than GPT-4 (0613). (Source: @AdaTheDev)
- Cost-Effectiveness of pplx-7b Model: Aravind Srinivas points out that the pplx-7b model is significantly cheaper than GPT-4-1106-preview, according to the latest LLM performance leaderboard. (Source: @AravSrinivas)
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What is GPT-4-1106-preview and how does it differ from other GPT models?
GPT-4-1106-preview is part of the GPT-4 Turbo series developed by OpenAI, offering improved structured output capability, better instruction following, support for parallel function calling, and reproducibility. It is trained on data up to April 2023, making it more up-to-date than some other models. Compared to GPT-3.5 and earlier GPT-4 models, it excels in complex reasoning tasks and misinformation mitigation.
How can GPT-4-1106-preview enhance my application's performance?
With its ability to generate structured outputs in JSON format, GPT-4-1106-preview can improve the functionality of applications requiring systematic analysis and function calling. Its improved instruction-following capabilities and support for parallel function calling make it highly efficient for complex tasks, enhancing both performance and user experience.
What are the key benefits of GPT-4-1106-preview's structured output capability?
The structured output capability of GPT-4-1106-preview allows it to produce outputs in JSON format, which is crucial for tasks requiring precise data manipulation, function calling, and systematic analysis. This feature significantly improves the model's reliability and performance in various applications.
Can GPT-4-1106-preview produce reproducible outputs?
Yes, GPT-4-1106-preview supports reproducibility and parallel function calling, ensuring consistent and efficient performance across tasks. This feature is particularly beneficial for applications requiring deterministic outputs for testing and quality assurance purposes.
What types of applications can benefit from using GPT-4-1106-preview?
Applications that require complex reasoning, structured data output, precise instruction following, and misinformation mitigation can significantly benefit from GPT-4-1106-preview. This includes, but is not limited to, chatbots, content generation tools, data analysis platforms, and educational software.
How up-to-date is the training data used for GPT-4-1106-preview?
GPT-4-1106-preview is trained on data up to April 2023, making it one of the most current models available in the GPT-4 series. This ensures that it has a broad and recent knowledge base to draw from, enhancing its understanding and responses.
Where can I integrate GPT-4-1106-preview into my applications?
You can integrate GPT-4-1106-preview into your connectivity apps and other applications through platforms like Telnyx. For more information on how to get started with integration, visit Telnyx's documentation.
How does GPT-4-1106-preview handle misinformation?
GPT-4-1106-preview is designed to outperform earlier models in complex reasoning tasks and misinformation mitigation. It employs advanced algorithms to evaluate and generate responses, reducing the likelihood of propagating inaccurate information.
Is GPT-4-1106-preview suitable for educational purposes?
Yes, GPT-4-1106-preview's advanced capabilities make it highly suitable for educational applications, providing accurate and reasoned responses that can aid in learning and research. Its structured output capability also allows for the creation of interactive learning tools.