Kimi K3
Kimi K3 is Moonshot AI’s most capable model, built for frontier intelligence scenarios such as software engineering, knowledge work, deep reasoning, and multimodal understanding. The model has 2.8 trillion parameters and uses Kimi Delta Attention, a hybrid linear attention mechanism, along with Attention Residuals for long-context performance. Kimi K3 supports a 1 million token context window, making it useful for analyzing large codebases, long documents, complex knowledge bases, and multi-step workflows. It includes native visual understanding for images and videos, with support for structured message formats, base64 image input, uploaded video files, and multimodal reasoning. Developers can use Kimi K3 through an OpenAI-compatible API with support for streaming, structured JSON output, partial mode, custom tools, dynamic tool loading, and automatic context caching.
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MiniMax M3
MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.
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Gemini 3.6 Flash
Gemini 3.6 Flash is Google’s newest Flash model built for efficient, reliable, production-scale AI agents. The model improves on Gemini 3.5 Flash with stronger coding, knowledge work, multimodal performance, computer use, and agentic workflow execution. Gemini 3.6 Flash is designed to use fewer output tokens, take fewer reasoning steps, reduce unnecessary tool calls, and lower the cost of complex AI tasks. It supports document parsing, chart analysis, data analysis, report drafting, code migrations, visual understanding, and multi-agent orchestration. The model is available through the Gemini API, Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise app, and the Gemini app. Built for developers and enterprises, Gemini 3.6 Flash helps teams build faster, lower-cost, and more capable AI agents across coding, analysis, productivity, and multimodal workloads.
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Grok 4.5
Grok 4.5 is SpaceXAI’s advanced AI model built for coding, agentic tasks, engineering work, and knowledge-intensive productivity. The model is trained on coding, science, engineering, and math data, with reinforcement learning focused on multi-step software engineering and technical workflows. It is designed to handle real-world development tasks such as debugging, Rust and C/C++ work, terminal tasks, long-running agentic rollouts, and end-to-end app creation from a single prompt. Grok 4.5 is also built for fast serving, token efficiency, and lower-cost execution, with pricing based on input and output token usage. Beyond coding, the model supports business productivity tasks in Grok Build, including Excel modeling, PowerPoint diagram creation, Word writing, and research-assisted office workflows. Available through Grok Build, Cursor, and the SpaceXAI API console, Grok 4.5 gives developers and teams a high-performance model for building software, automating work, and more.
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