Home - LLM models - Page 10
We may earn compensation if you purchase via some links
Enjoy professional-level intelligence with extreme speed and efficiency (and at a reduced cost). This model uses 30% fewer tokens and is very good at agentic coding
An open-source language model optimized for reasoning. Benefit from advanced natural language processing and complex problem-solving capabilities
An open-source model optimized for autonomous coding that rivals Claude Sonnet 4.5 while costing 10 times less. Specialized in multilingual coding, tool usage, and long-horizon planning
A powerful LLM model with 236 billion parameters. It performs brilliantly in mathematics, coding and reasoning, with very competitive API pricing ($0.14/million tokens)
Anthropic's premium model for code, agents, and computer use: hybrid reasoning (instant or deep responses), advanced memory management, and execution of long workflows with fewer tokens
Explore the open-source AI reasoning models created by OpenAI. With a complete thought chain that can be customized for specific applications under the Apache 2.0 license. Two versions available: gpt-oss-120b…
An AI that could become a free and open source alternative to ChatGPT
An AI model specialized in mathematics, with advanced reasoning capabilities and the ability to solve complex problems. Soon to be bilingual (English-Chinese)
Llama 3 is a high-performance open-source LLM model designed by Meta AI, with 400 billion parameters on the counter
Deepseek's open source LLM with 671 billion parameters specializing in mathematics and reasoning. This model is effective at processing long contexts and performs well in code, logic, and formal proofs
The new agentic and open-source model from Moonshot AI (supported by Alibaba). It is capable of step-by-step reasoning, dynamically using tools, and conducting research, coding, or writing workflows involving hundreds…
An open-source language model inspired by OpenAI o1, based on Meta's Llama-3.1. Uses reasoning chains to solve complex problems, with an accuracy of around 70%.