AI Intelligence

Fast, efficient model for visual reasoning, precise computer use, and clear, natural writing.

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

Open-weight mixture-of-experts model with about 2.5B active parameters for local coding agents

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

October 17 update of DeepSeek V4.1 Flash with improved reasoning, coding, agentic tasks, and visual understanding

Inception's diffusion reasoning model for chat, multi-step problem solving, and 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.

NVIDIA Nemotron 3.5 Super reasoning model (120B total, 12B active) served with text-only input

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

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.

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.

LightOnOCR-3-0.8B is the lightest model of LightOn's LightOnOCR-3 family, with the same layout and visual understanding features as its larger siblings.

Fast Claude model for responsive assistance, classification, and lightweight agents

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

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

Mistral's 1T-parameter multimodal MoE for reasoning, coding, and agentic work

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

Sparse mixture-of-experts reasoning model with 23B active parameters for coding and agentic workflows

Aleph Alpha's German and English mixture-of-experts reasoning model (78B total, 3.46B active) for chat, RAG and agents

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

Near-Astra performance for complex coding, computer use, and professional work at a lower cost.

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

Fast Claude model for everyday coding, agents, and knowledge work

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

Meituan's multimodal reasoning model for coding and agent tasks, with image understanding and a 1M-token context window

Image, video, and audio understanding with visual grounding, reasoning, and function calling

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

Claude model for long-running agentic coding and knowledge work

Specialized model from Fireworks built on Kimi K3, producing shorter reasoning traces with approximately 40% fewer tokens while maintaining comparable quality

OpenAI's most efficient model for focused, high-volume tasks

OpenAI model for complex coding and agentic workflows

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

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

Upstage's compact, cost-efficient model for agentic use

xAI's frontier model for long-running agents, coding, knowledge work, and visual projects

MiMo pro model for strong multimodal reasoning and agent execution

Fast coding model

Speech-to-text model with word-level timestamps, speaker diarization, multichannel audio, and streaming

Blended multimodal model that runs multiple language models in parallel and returns a synthesized answer