Minerva vs ChatGPT Plugins
Dive into the comparison of Minerva vs ChatGPT Plugins and discover which AI Large Language Model (LLM) tool stands out. We examine alternatives, upvotes, features, reviews, pricing, and beyond.
In a comparison between Minerva and ChatGPT Plugins, which one comes out on top?
When we compare Minerva and ChatGPT Plugins, two exceptional large language model (llm) tools powered by artificial intelligence, and place them side by side, several key similarities and differences come to light. ChatGPT Plugins is the clear winner in terms of upvotes. ChatGPT Plugins has garnered 13 upvotes, and Minerva has garnered 6 upvotes.
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Minerva

What is Minerva?
Minerva is a large language model from Google Research built to solve math and science questions through step-by-step written reasoning. It reads problems that mix plain English with LaTeX notation, then writes out solutions involving arithmetic, algebra, and symbolic steps. The model was trained on scientific papers and web pages where mathematical formatting was kept intact, rather than stripped during preprocessing.
Most math-capable models lean on external tools like Python interpreters or calculators at inference time. Minerva takes the opposite bet: it generates full worked solutions from the model weights alone, using chain-of-thought prompting and majority voting across multiple sampled answers. That informal approach covers a wider range of problem types than formal theorem provers, but the trade-off is answers cannot be machine-verified the way Coq or Lean proofs can.
Researchers studying quantitative reasoning in language models use Minerva as a reference point for STEM benchmark performance. The public sample explorer hosts 110 solved problems across algebra, physics, chemistry, and other topics, so anyone can read through how the model arrived at each answer. Educators and ML engineers reviewing benchmark methodology will find the published MATH, MMLU-STEM, GSM8k, and OCWCourses scores useful for comparing against newer models.
ChatGPT Plugins

What is ChatGPT Plugins?
OpenAI follows an iterative deployment philosophy, and as part of this approach, it is gradually releasing plugins for ChatGPT. The purpose of this gradual release is to study the real-world use of the plugins, assess their impact, and identify any safety and alignment challenges that may arise. Getting these aspects right is essential for OpenAI to achieve its mission.
Since the launch of ChatGPT, users have expressed interest in having access to plugins, and many developers are experimenting with similar ideas. OpenAI is initially rolling out plugins to a small set of users and plans to gradually increase access as it learns more. After an alpha period, API users who want to integrate plugins into their products will also have access. OpenAI is excited to build a community that will help shape the future of the human-AI interaction paradigm.
Developers who have been invited off the waitlist can use OpenAI's documentation to build a plugin for ChatGPT. Once the plugin is created, it is listed in the prompt shown to the language model, along with documentation that instructs the model on how to use each one. The first set of plugins has been created by Expedia, FiscalNote, Instacart, KAYAK, Klarna, Milo, OpenTable, Shopify, Slack, Speak, Wolfram, and Zapier.
Minerva Upvotes
ChatGPT Plugins Upvotes
Minerva Top Features
Built on PaLM with 118GB of arXiv papers and math-formatted web pages in training data
Scores 50.3% on the MATH benchmark at 540B parameters, up from a prior best of 6.9%
Generates solutions with arithmetic and symbolic steps without calling a calculator or Python interpreter
Uses chain-of-thought prompting, few-shot examples, and majority voting across sampled outputs
Public sample explorer shows 110 worked problems across 11 topics including algebra, physics, and chemistry
Reaches 75% on MMLU-STEM and 78.5% on GSM8k, both ahead of published prior state of the art
ChatGPT Plugins Top Features
Real-time Information Access: Plugins enable ChatGPT to access up-to-date information, making it more useful and informed.
Computation Capability: Perform computations or run code snippets directly within the chat, enhancing problem-solving abilities.
Third-party Service Interaction: Interact with services like Expedia, FiscalNote, or Instacart, expanding the range of tasks ChatGPT can assist with.
Community Building: OpenAI aims to build a community of developers and users to shape the future of human-AI interaction through plugins.
Gradual Rollout: A cautious rollout approach to study real-world use, impact, and safety, ensuring a responsible deployment of this new feature.
Minerva Category
- Large Language Model (LLM)
ChatGPT Plugins Category
- Large Language Model (LLM)
Minerva Pricing Type
- Free
ChatGPT Plugins Pricing Type
- Freemium
