Models

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

Reasoning-first Gemini preview for agentic coding and complex problem solving

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

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

New Gemini flash lane bringing frontier-style multimodal reasoning to cheaper runs

GLM vision model for visual reasoning, documents, and multimodal agents

GLM vision model for visual reasoning, documents, and multimodal agents

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

Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents

Fast Gemini workhorse for multimodal apps where latency and price matter