Models

Multimodal Kimi model with 1M context and always-on reasoning for coding, 3D creation, financial research, and agentic work

Frontier multimodal coding model with 1M context window and tunable thinking depth

Google's flagship reasoning model for complex software engineering, deep math and science, and long-horizon autonomous agents

Muse Wonder Full is the most capable model in Meta's Muse Wonder series, built for long-running professional agents and ultra-long-horizon software engineering. It shares Muse Wonder's Active Memory and Active Focus capabilities and generally scores higher on Meta's agentic and coding evaluations.

Muse Wonder is a frontier multimodal reasoning model from Meta for personal and professional agents, long-horizon coding, and computer use. It combines Active Memory, which carries relevant context across conversations, with Active Focus, which keeps it working through blockers toward a goal.

Image model for prompt-driven generation, multi-turn editing, and visual design workflows

Cost-efficient video model for text-to-video and image-to-video generation

Frontier multimodal coding model with 1M context window and tunable thinking depth

High-throughput edition of Qwen3.8 Max for coding, professional work, multimodal understanding, and long-running agent workflows

Qwen omni model for text, vision, audio, and multimodal agent tasks

Kimi coding model with more efficient thinking and up to 1M context, available through Kimi Code

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

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It improves long-horizon agent collaboration, instruction following, and coding efficiency relative to Muse Spark 1.2.

2026-09-02 upgraded snapshot of Qwen3.8 Max with stronger coding, collaborative agents, and multimodal document understanding

Video generation and editing model for scene extension, frame interpolation, and reference-guided multimodal control

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

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

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

Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.

2.4-trillion-parameter MoE flagship for coding, professional work, multimodal understanding, and long-horizon agentic workflows

ByteDance multimodal audio-video model with up to 30-second single-pass generation, multi-round extension, reference inputs and timestamp-level editing.

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

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

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

Preview Qwen flagship for million-token multimodal reasoning and long-horizon agentic workflows

Lightweight multimodal Qwen model for high-throughput text, image, and video tasks

Video generation and editing model for fast, conversational text- and image-to-video workflows

Faster ByteDance Seed 2.1 model for multimodal reasoning and latency-sensitive agent workflows

ByteDance Seed model optimized for character-driven dialogue and consistent conversational behavior

Rolling ByteDance Seed model for rapidly updated reasoning, coding, and agent capabilities

Flagship ByteDance Seed 2.1 model for complex multimodal reasoning, coding, and agents

Multimodal Qwen workhorse for long-context agents, visual inputs, and coding

Video model for text-to-video, image-to-video, and reference-to-video generation with optional voice references

Image model for prompt-driven generation, editing, and visual design workflows

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

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

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

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

Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space

Agentic model for autonomous multi-step research, synthesis, and cited reports

Maximum-comprehensiveness agentic researcher for multi-step investigation, synthesis, and cited reports

Vision-language model for embodied reasoning: spatial understanding, task planning, and physical-world agentic robotics

Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.

Earlier Qwen multimodal workhorse for million-token agent and document tasks

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

Video model for prompt-guided generation, editing, and motion workflows

High-quality, low-latency Live API model for real-time dialogue and voice-first AI applications

MiMo omni model for text, image, video, audio, and agents

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

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