AI Foundation Models & LLM Specifications
Cataloged specifications and pricing snapshots per 1M tokens, prompt caching rates, and tool-calling support. Discover which models best power your MCP tools and agent loops.
610
Foundation Models
467
MCP Tool-Call Ready
350
Reasoning & Thinking
317
Open Weights (HuggingFace)
Showing 181-216 of 610 models
Open MiMo model for multimodal coding agents and long-context automation
Stronger MiMo Pro tier for multimodal reasoning and coding-agent execution
Qwen vision-language model for visual reasoning, documents, and agent tasks
Multimodal embedding model mapping text, images, video, audio, and PDFs into a unified embedding space
Speech generation model for controllable voice, narration, and audio delivery
Speech generation model for controllable voice, narration, and audio delivery
Speech generation model for controllable voice, narration, and audio delivery
Maximum-comprehensiveness agentic researcher for multi-step investigation, synthesis, and cited reports
Agentic model for autonomous multi-step research, synthesis, and cited reports
Image model for prompt-driven generation, editing, and visual design workflows
Image model for prompt-driven generation, editing, and visual design workflows
Multimodal Kimi workhorse for agent loops, coding tasks, and visual context
Flagship Qwen model for complex reasoning, coding, and agentic workflows
Tencent Hy reasoning model for coding, instruction following, and agent tasks
xAI's default Grok for chat, coding, agentic tools, and lower hallucination risk
Open multimodal Qwen MoE for local agents that need vision, audio, and code
Stronger Opus tier for advanced software work and high-stakes reasoning
Fast Grok coding model tuned for agentic engineering and iterative edits
Efficient model for low-latency assistance, extraction, and routine automation
Efficient model for low-latency assistance, extraction, and routine automation
Low-latency speech generation with steerable prompts and expressive audio tags
Vision-language model for embodied reasoning: spatial understanding, task planning, and physical-world agentic robotics
Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.
Strong GLM coding model for agentic engineering, terminals, and repository generation
Higher-fidelity Grok Imagine image model for prompt-driven generation, editing, and visual design workflows
Earlier Qwen multimodal workhorse for million-token agent and document tasks
Open Gemma instruction model for efficient chat and self-hosted deployments
Largest Gemma 4 instruction model for open, self-hosted chat and reasoning
StepFun flash model for efficient multimodal reasoning, coding, and tool use
Open Gemma instruction model for efficient chat and self-hosted deployments
Open Gemma instruction model for efficient chat and self-hosted deployments
Reasoning-optimized 398B MoE agent model with extended thinking for long-horizon and multi-turn tool use
Fast GLM vision model for screenshots, documents, and multimodal agent tasks
Video model for prompt-guided generation, editing, and motion workflows
Code editing dLLM for autocomplete (FIM) and next-edit suggestions
High-quality, low-latency Live API model for real-time dialogue and voice-first AI applications