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Solving Quantitative Reasoning Problems with Language Models

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Language models have achieved remarkable performance on a wide range of tasks that require natural language understanding. Nevertheless, state-of-the-art models have generally st

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Solving Quantitative Reasoning Problems with Language Models

Added 1 June 2026

Overview

Minerva is a large language model pretrained on general natural language data and further trained on technical content. It achieves state-of-the-art performance on college-level mathematics, science, and engineering benchmarks without using external tools. The model is introduced in a research paper from the community.

Best for

Best for
Researchers and developers exploring quantitative reasoning in language models

Use cases

  • Solving college-level math problems
  • Answering science and engineering questions
  • Performing quantitative reasoning without external calculators

Notes

Minerva is a large language model pretrained on general natural language data and further trained on technical content. It achieves state-of-the-art performance on college-level mathematics, science, and engineering benchmarks without using external tools. The model is introduced in a research paper from the community.

Use cases

  • Solving college-level math problems
  • Answering science and engineering questions
  • Performing quantitative reasoning without external calculators

Pros

  • State-of-the-art performance on technical benchmarks
  • No reliance on external tools or calculators
  • Trained on specialized technical content

Cons

  • Requires significant computational resources for inference
  • Primarily a research contribution, not a production-ready tool
  • May not generalize to all quantitative reasoning tasks

Indexed from awesome-llm and enriched against its public facts.

Pros

  • State-of-the-art performance on technical benchmarks
  • No reliance on external tools or calculators
  • Trained on specialized technical content

Cons

  • Requires significant computational resources for inference
  • Primarily a research contribution, not a production-ready tool
  • May not generalize to all quantitative reasoning tasks