Step By Step Math Problem Solver

via “math problem solving with step-by-step explanations”

All-in-one AI assistant extension with GPT-4 and Claude.

Unique: Provides step-by-step math solutions with equation rendering directly in browser sidebar, supporting both text and image input without requiring separate math solver tools

vs others: More educational than Wolfram Alpha because it emphasizes step-by-step working and explanations rather than just final answers, though less comprehensive for symbolic computation

via “mathematical problem solving with step-by-step verification”

text-generation model by undefined. 38,71,385 downloads.

Unique: Trained via RL to optimize for mathematical correctness with explicit intermediate step generation; learns to recognize and correct errors during reasoning rather than committing to incorrect paths

vs others: Outperforms GPT-4 on MATH and AIME benchmarks (94.3% vs 80%+ on AIME) through learned reasoning allocation; provides more transparent reasoning than Gemini while maintaining higher accuracy

via “mathematical problem solving with step-by-step derivation”

Talk to Claude, an AI assistant from Anthropic.

via “mathematical-problem-solving-with-step-by-step-reasoning”

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

Unique: Implements explicit reasoning phase specifically optimized for mathematical decomposition, allowing the model to verify intermediate steps before producing final answers, rather than generating answers directly.

vs others: More reliable for complex math than GPT-4 due to explicit verification phase, and more transparent than o1 (which hides reasoning) by allowing users to request step-by-step explanations.

via “mathematical problem solving with step-by-step verification”

DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

Unique: Achieves o1-level mathematical reasoning performance with fully transparent step-by-step verification, enabling educators and students to validate each calculation. The 671B parameter model with sparse activation maintains reasoning coherence across multi-step proofs while keeping inference costs lower than dense alternatives.

vs others: Superior to GPT-4 on complex math problems due to explicit reasoning, and more transparent than o1 which hides intermediate steps, making it ideal for educational and verification use cases.

via “mathematical problem solving with step-by-step derivations”

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...

Unique: Applies reasoning_effort to control derivation depth and detail, enabling educators to generate solutions at varying levels of explanation without prompt changes. This differs from static math solvers (Wolfram Alpha) by providing reasoning traces and educational explanations.

vs others: More educational than symbolic solvers (shows reasoning); more flexible than static problem banks; enables personalized explanation depth through reasoning_effort parameter.

via “mathematical problem solving with step-by-step proof generation”

Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...

Unique: Allocates specialized mathematical reasoning experts through MoE routing, enabling step-by-step proof generation with explicit symbolic and logical reasoning rather than pattern-matching mathematical solutions

vs others: Provides verifiable step-by-step mathematical reasoning unlike standard LLMs, though with higher latency and no formal correctness guarantees

via “mathematical problem-solving with step-by-step derivation”

DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new...

Unique: Distills R1's mathematical reasoning capability to generate complete step-by-step derivations with intermediate justifications, making mathematical problem-solving transparent and verifiable

vs others: Provides more detailed reasoning than standard LLMs and more cost-effective reasoning than o1-mini while maintaining educational value through explicit derivation steps

via “mathematical-problem-solving-with-step-by-step-reasoning”

[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...

Unique: Phi-4's reasoning architecture is specifically optimized for mathematical problem decomposition, using transformer attention patterns trained on mathematical reasoning datasets to generate explicit intermediate steps that mirror human problem-solving approaches, enabling educational validation and debugging of mathematical logic.

vs others: Phi-4 delivers math reasoning comparable to GPT-4 at 1/10th the inference cost and 5x faster latency, making it practical for real-time tutoring systems and educational platforms where cost-per-query is a constraint.

via “step-by-step math problem solving”

Best AI math solver, calculator & tutor.

Unique: Utilizes a hybrid approach combining symbolic computation with natural language processing to provide detailed solutions and explanations, which is not common in typical math solver tools.

vs others: More comprehensive in explanation than traditional calculators, as it provides step-by-step guidance rather than just final answers.

via “step-by-step math problem solver”

via “mathematical-problem-solving-with-steps”

via “math problem solving with step-by-step explanation”

Unique: Emphasizes pedagogical step-by-step explanation alongside answers, using Claude's instruction-following to break down reasoning at each stage rather than providing only final results. Includes alternative method explanations to show multiple solution paths.

vs others: More educational than Wolfram Alpha because it explains reasoning at each step; more accessible than hiring a tutor while providing personalized problem walkthroughs

via “step-by-step-equation-solving”

via “mathematical-problem-solving”

via “step-by-step equation solving”

via “math problem solving”

via “mathematical reasoning and problem solving”

via “mathematical problem solving”

via “math-and-calculation-assistance”