Best AI tools forLLM models

« An LLM expert in coding, research, writing, and translation on 200k tokens. High-performing in agentics, it automates your tasks, generates presentations, and adapts the tone according to the context (professional or creative)  »

« An open-source LLM with 200 billion parameters and exceptional performance (at low cost). 2x faster and 8x cheaper than most of its competitors »

« 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 of steps »

« Baidu's native multimodal model, capable of understanding and generating text, images, sound, and video. It includes instruction following, factual reasoning, agentic planning, and the use of tools for creation, analysis, and global-level services »

« The upgraded version of Grok 4, with hallucinations reduced by 3 times, superior emotional intelligence, and creativity increased by 600 points. It is available for free at grok.com and X »

« Google's most intelligent multimodal model: advanced reasoning, deep contextual understanding, autonomous agents, visual coding, and Deep Think mode. It performs particularly well for agentic coding »

« 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 »

« Explore a range of height multimodal AI models created by Amazon. Generate text, images and video with high performance thanks to integration with AWS infrastructure »

« Code faster with two open-source models (1.3B and 123B parameters) and a CLI agent that explores, modifies, and executes multi-file changes in natural language. Features 256K context tokens and Git integration »

« 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  »

« A family of open-source encoder-decoder models with 2 to 9 billion parameters, based on Gemma 2, with higher inference efficiency than decoder-only models. Available on Hugging Face, Kaggle, and Vertex AI »

« Build specialized AI agents with a family of open-source models optimized for multi-agent systems, hybrid MoE, and with context up to 1M tokens. Enjoy 4x higher throughput than Nemotron 2 Nano. »