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

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

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

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

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

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

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

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

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

Fast Gemini workhorse for multimodal apps where latency and price matter

Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents

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