Models

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Preview Gemini flagship for complex reasoning, coding, and rich multimodal prompts

Nemotron multimodal model for visual reasoning and agentic AI workflows

Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents

Fast Gemini workhorse for multimodal apps where latency and price matter

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

Flagship model for demanding analysis, coding, and production agent workflows

Efficient model for low-latency assistance, extraction, and routine automation