« A powerful open-source model (1,000 billion parameters) that understands text and images and can analyze technical drawings and satellite imagery. It is capable of fixing vulnerable code and speaks more than 160 languages. Also has excellent agent capabilities »
Best AI tools forLLM models
AI models to test and tools to learn how to master them
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AdsCreator.com
« Generate ad creatives ready for Meta, Google, Stories, and Reels from a single URL. AI automatically extracts your colors, fonts, brand tone, and creates dozens of on-brand variations in seconds »
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« A series of (multimodal) LLM models able to process text and images for reasoning tasks. They were developed and released as open source by Xiaomi. Manage code, searches, interfaces, layouts, 3D, agents, and graphical tasks. Supports up to one million tokens »
« A fast and cost-effective model designed for code, agents, and complex workflows, with a 1-million-token context and significant improvements on long-running tasks and multi-step execution. Compared to its predecessor, this model scores 9 points higher on FrontierCode 1.1 and 16 points higher on DeepSWE v1.1 »
« A 30-billion-parameter agent-based model capable of running directly on a Mac or PC equipped with a consumer-grade GPU, with no internet connection required. Available as open source under the Apache 2.0 license »
« Designed for intensive tasks, this model from Google’s Gemini family outperforms its predecessor in token efficiency while improving performance in coding and knowledge-based tasks. With a 1-million-token context, full multimodality, and better agentic task performance »
« Microsoft’s new reasoning model, trained from scratch and optimized for code. It rivals the best models on SWE-Bench Pro and AIME 2025, while remaining medium-sized and computationally efficient »
« Power up your code agents with a 128-billion-parameter model featuring a 256,000-token context window, which excels at coding, reasoning, and following instructions. This model requires only 4 GPUs to run and achieves a score of 77.6% on SWE-Bench Verified »
« The first model developed by Meta Superintelligence Labs, built from scratch in nine months and natively multimodal (text, image, voice). Its “Contemplating” mode coordinates multiple sub-agents in parallel and is already powering Meta AI on Facebook, Instagram, and WhatsApp »
« Take advantage of enhanced audio and visual understanding to create comprehensive multimodal applications, ranging from image analysis to audio interpretation. The open-source E2B and E4B models offer optimal memory capacity and computational efficiency. Perfect for inference on devices with limited resources »
« This open-source model combines reasoning, image analysis, and advanced coding into a single tool. Powerful and flexible, it can handle long queries and generate more direct and effective responses. A robust alternative to the best models on the market »
« This version of Grok brings together four professor-level agents who reason together before responding. They correct each other, break down problems, and rely on real-time web search and coding tools to provide more reliable answers »
« 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. »