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

NVIDIA vision-language reasoning model for text, image, and video understanding and agentic tool use

Muse Spark Open is an 816B total / 42B active open-weight multimodal reasoning model from Meta for coding and long-horizon agentic work, with 1M-token context.

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

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.

First MoE MiniCPM-V model for single-image, multi-image and video understanding

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

Compact MiniCPM-V model for single-image, multi-image and video understanding

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

MiMo Flash model for multimodal coding agents and long-context automation

Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution

MiMo pro model for strong multimodal reasoning and agent execution

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

StepFun's next-generation flagship base model for coding and professional knowledge work, with native text, image, and video input and a 1M-token context window

Native multimodal hybrid MoE model for image and video understanding, reasoning, and visual agents

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

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

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

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

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

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

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

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

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

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

Lower-latency Kimi Code variant for interactive edits and coding-agent loops

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

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

Newer StepFun flash model for faster agents, coding, and multimodal prompts

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

Open Nemotron omni model combining reasoning with text, vision, and audio

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

Open MiMo model for multimodal coding agents and long-context automation

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