Best AI tools forLLM models

« 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 »

« This open-weight model, with 754 billion parameters, is designed for long and complex engineering tasks: it can operate autonomously for up to 8 hours straight, from planning through to final delivery. As the world’s first open-source model on WE-Bench Pro and NL2Repo, it rivals Claude Opus 4.6 in code quality  »

« Run a 35-billion-parameter MoE model with only 3 billion parameters actually activated, while achieving coding, vision, and reasoning performance on par with much larger models. Optimized for agentic coding, multimodal perception, and very long contexts (up to over a million tokens) »

« This open-source model takes agent-based programming even further with multi-file editing, 256K of context, and the generation of animated front-end interfaces. It also features swarms of up to 300 sub-agents capable of performing tasks continuously  »

« This Mixture-of-Experts model, with approximately 1 trillion parameters, features a 1M-token context, virtually infinite Engram memory, and multimodal capabilities for text, images, and video. It aims to achieve performance scores comparable to Claude Opus while remaining significantly more affordable (to be released under the Apache 2.0 license)  »

« 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 »

« Baidu's flagship model is more cost-effective and powerful: it requires only one-third of the resources of its competitors and achieves a score of 99.6 on AIME26. It outperforms DeepSeek V4 Pro on several practical benchmarks and ranks first among Chinese models on LMArena Text  »

« 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 »

« An open-source model designed for code and long-running tasks, with a context window of up to 1 million tokens. This Mixed Expert (MoE) LLM handles complex projects, analyzes entire repositories, and performs multi-step reasoning. It is available as open source under the MIT license »