Models

Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows

Open-weight experimental preview of the Qwen4 architecture: hybrid-attention MoE (125B total, 6B active) with vision encoder for coding, agent tasks, and image and video understanding

Native multimodal GLM model for efficient coding and long-horizon agent tasks

Dense 27B vision-language model for coding, agent tasks, and image and video understanding

High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning

Fast Gemini model balancing multimodal reasoning, tool use, and cost

Fast Gemini model balancing multimodal reasoning, tool use, and cost

Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work

Coding-focused Kimi model, stronger on long-horizon repo work with less overthinking

MiniMax multimodal model for long-context coding, perception, and agent planning

Fast Gemini model balancing multimodal reasoning, tool use, and cost

Low-latency Gemini model for high-volume multimodal and agent workloads

Qwen vision-language model for visual reasoning, documents, and agent tasks

Multimodal Kimi workhorse for agent loops, coding tasks, and visual context

Open multimodal Qwen MoE for local agents that need vision, audio, and code

Fast GLM vision model for screenshots, documents, and multimodal agent tasks

Qwen vision-language model for visual reasoning, documents, and agent tasks

Qwen instruction model for multilingual chat, reasoning, and tool use

Large open Qwen multimodal MoE for visual agents and long technical tasks

Earlier Kimi frontier model for long-context agents, coding, and multimodal work

Multimodal reasoning model for visual analysis, planning, and tool use

Fast Gemini workhorse for multimodal apps where latency and price matter

Google's proven reasoning model for coding, math, and multimodal analysis