| id | title | sidebar_label |
|---|---|---|
choosing-right-model |
Choosing the Right Model for Your Use Case |
Choosing the Right Model |
Welcome to our guide on selecting the most suitable model for your needs within the GPT for Work ecosystem. With a range of extensions like Sheets, Docs, Excel, and Word, it's essential to understand which model aligns best with your requirements. Whether you're prioritizing accuracy, speed, or specialized knowledge, this article will help you navigate the decision-making process.
This article explores the various factors to consider when choosing a model within the GPT for Work extensions. Each model comes with its own strengths and limitations, and understanding these nuances will empower you to make informed decisions that enhance your workflow efficiency and output quality.
When selecting a model, several key factors come into play when selecting a model for your use case. Click each factor below to find out more about what to consider when choosing a model for your use case:
Use Case Specificity
Determine the specific tasks or projects you intend to use the model for. Different models may be more adapted to certain domains, such as general writing, technical content, or creative endeavors.
Consider these use cases:
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Word/Docs
- Writing and Editing Copy: Determine if your primary task involves drafting new content or refining existing text. Some models excel at generating fresh content, while others are better suited for editing and refining.
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Excel/Sheets
- Data Preparation: Assess whether your workflow involves cleaning lists, extracting entities, or normalizing formats. Certain models are adept at processing structured data and performing data cleaning tasks efficiently.
- Analysis: Consider if your use case involves summarizing text, classifying documents, or categorizing information. Models tailored for analytical tasks can provide accurate summaries, classifications, and categorizations.
Accuracy vs. Speed
Assess whether you prioritize accuracy or speed in your workflow. Some models may sacrifice a bit of accuracy for faster response times, while others prioritize precision but may take longer to generate outputs.
Model Size and Complexity
Larger models often provide more nuanced and contextually relevant responses but may require more computational resources and time for processing. Evaluate whether the benefits of a larger model outweigh the potential drawbacks for your use case.
Requires API Key
Whether or not an API key is required will affect the price and billing when purchasing choosing a GPT for Work-supported model, because, without an API key, a purchase pack must be purchased along with the model. Use the Cost estimator to find out which model is most cost-effective for your inputs.
Compare the available models within the GPT for Work extensions, taking into consideration the factors mentioned above. Click on each task type in the table below to see a list of all available GPT for Work models for each use case.
| Use Cases | Models to use for... |
|---|---|
| Excel | Performing bulk operations on data in workbooksgpt-3.5-turbo (0125)gpt-4 gpt-4-1106-vision-preview (with GPT_VISION) gpt-4-turbo text-embedding-ada-002 (with GPT_MATCH) gpt-3.5-turbo (0613) gpt-4 gpt-4-turbo sonar-small-online (with GPT_WEB and Web browsing bulk tool) |
| Word | Chatting with Microsoft Wordgpt-3.5-turbo (0125)gpt-4 gpt-4-turbo |
| Sheets | Performing bulk operations on data in spreadsheetsbabbage-003 (fine-tuned)davinci-002 (fine-tuned) gpt-3.5-turbo (0125) gpt-4 gpt-4-1106-vision-preview (with GPT_VISION) gpt-3.5-turbo-instruct gpt-3.5-turbo (fine-tuned) gpt-4-turbo text-embedding-ada-002 (with GPT_MATCH) claude-3-haiku claude-3-opus claude-3-sonnet gpt-3.5-turbo (0613) gpt-4 gpt-4-turbo sonar-small-online (with GPT_WEB and Web browsing bulk tool) |
| Docs | Integrated ChatGPTgpt-3.5-turbo (0125)gpt-3.5-turbo-instruct gpt-4 gpt-4-turbo Faster writing, editing, translationclaude-3-haikuclaude-3-opus claude-3-sonnet |