A comprehensive index of state-of-the-art artificial intelligence models, generative platforms, and products. Search and filter by category to find the perfect tool for your workflow.
Developed by Anthropic
Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for highly autonomous agents, long-horizon agentic work, knowledge work, complex coding, and end-to-end project orchestration.
Developed by Anthropic
Fast-mode variant of Opus 5 - identical capabilities with higher output speed at 2x pricing relative to regular Opus 5.
Developed by OpenAI
GPT-5.6 Luna is a cost-effective, high-volume language model by OpenAI designed for large-scale text generation workflows. Representing the nano model tier in the GPT-5 family, it delivers efficient processing and fast inference for automated pipelines, chatbots, and developers looking for cheap API solutions.
Developed by OpenAI
The latest advanced language model by OpenAI designed for superior reasoning, extensive context handling, and high-performance text generation.
Developed by OpenAI
An advanced generative model by OpenAI optimized for large context handling, complex reasoning, and high-performance text synthesis.
Developed by Tencent
Hy3 is a 295B-parameter Mixture-of-Experts (MoE) model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports configurable reasoning effort (no-think mode by default, plus low and high chain-of-thought modes for complex math, coding, and multi-step problems). Features a 256K context window with long-horizon task capabilities, improved coreference resolution, multi-turn constraint tracking, and stable tool-calling. Emphasizes grounded, anti-hallucination behavior that answers when grounded and flags missing evidence.
Developed by Moonshot AI
Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.
Developed by DeepReinforce
Ornith-1.0 is a self-improving family of open-source models specially designed for agentic coding tasks. Developed by DeepReinforce, Ornith spans compact 9B and 31B dense edge-deployable models to 35B and 397B Mixture-of-Experts (MoE) models. Built on a self-improving RL framework, the model co-evolves task-specific agentic scaffolds alongside solution rollouts, achieving state-of-the-art results on benchmarks such as Terminal-Bench 2.1 and SWE-Bench Verified.
Developed by Alibaba Qwen
Qwen3-Coder-Next is a coding-focused language model from Alibaba's Qwen team, optimized for agentic coding workflows and local development.
