OpenRouter-style model index with deep metadata: pricing, context windows, architecture, and parameters.
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases.
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases.
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license.
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b.
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding.
The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning.
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks.
o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex, multi-step research tasks.
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding.
OpenAI o3-mini-high is the same model as o3-mini with reasoning_effort set to high.
The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning.
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities.
o4-mini-deep-research is OpenAI's faster, more affordable deep research model—ideal for tackling complex, multi-step research tasks.
OpenAI o4-mini-high is the same model as o4-mini with reasoning_effort set to high.
Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output.