OpenAI

GPT-5.6 Sol Pro is GPT-5.6 Sol run in OpenAI's pro reasoning mode, which performs more model work per request for difficult tasks that justify higher latency and token use. It is the same underlying model, with text and image input, text output and a context window of about 1.05M tokens.

GPT-5.5 is OpenAI's GPT-5 series model for coding and complex professional work. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and reasoning effort from none to xhigh.

gpt-oss-120b is OpenAI's open-weight Mixture-of-Experts language model with 117B total and 5.1B active parameters, released under the Apache 2.0 license. It takes text input and produces text output with a 128K-token context window, configurable low, medium and high reasoning, full chain-of-thought access and native tool use including function calling and structured outputs.

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for lower-latency inference. The model is trained in OpenAI’s Harmony response format and supports reasoning level configuration, fine-tuning, and agentic capabilities including function calling, tool use, and structured outputs.

OpenAI's multimodal flagship model with vision capabilities, strong reasoning, and broad knowledge. Popular for its balanced performance across tasks. Version: 2024-11-20.

OpenAI's cost-efficient small model that delivers GPT-4 level intelligence at a fraction of the cost. Ideal for high-volume applications requiring strong reasoning. Version: 2024-07-18.

GPT-5.2 is OpenAI's GPT-5 series model for complex professional work. It takes text and image input and produces text output, with a 400K-token context window, up to 128K output tokens and reasoning effort from none to xhigh.

GPT-5.3 Codex is OpenAI's coding model built on GPT-5.3 and optimized for agentic coding tasks in Codex and similar environments. It takes text and image input and produces text output, with a 400K-token context window, up to 128K output tokens and low to xhigh reasoning effort.

GPT-5.4 is OpenAI's GPT-5 series model for coding and complex professional work. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and reasoning effort from none to xhigh.

GPT-5.4 Mini brings the core capabilities of GPT-5.4 to a faster, more efficient model optimized for high-throughput workloads. It supports text and image inputs with strong performance across reasoning, coding, and tool use.

GPT-5.4 Pro is a version of OpenAI's GPT-5.4 that uses more compute to think harder and give more precise answers on complex, high-stakes tasks. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and medium to xhigh reasoning effort.

GPT-5.5 Pro is a version of OpenAI's GPT-5.5 that uses more compute to think harder and give more precise answers on complex tasks. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and medium to xhigh reasoning effort.

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, built for complex professional work such as reasoning, coding and agentic workflows. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and reasoning effort from none to max.

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced.

GPT-5.6 Terra Pro is the same underlying model as GPT-5.6 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

GPT-6 Astra is the top tier of OpenAI's GPT-6 family, built for demanding work such as complex reasoning, coding, computer use, research and document creation. It takes text and image input and produces text, with a 1.05M-token context window (up to 922K input and 128K output tokens) and configurable reasoning effort.

GPT-6 Astra with pro reasoning mode for difficult tasks that benefit from more model work. Supports text and image inputs with a 1.05M token context window. Pro mode can use more tokens and take longer than standard Astra.

GPT-6 Luna is OpenAI's most efficient GPT-6 model for focused, high-volume tasks. It is suited for chat, classification, and lightweight agentic workflows, with a 1.05M token context window (922K input, 128K output), text and image inputs, and capable reasoning for its price tier.

GPT-6 Sol is built for complex coding and agentic workflows. It is OpenAI's GPT-6 coding and agent model, with a 1.05M token context window (922K input, 128K output), support for text and image inputs, and reasoning effort from none through max.

GPT-6.1 Sol delivers near-Astra performance at a lower cost for complex coding, computer use, and professional work. It has a 1.05M token context window (922K input, 128K output), support for text and image inputs, and reasoning effort from low through max.

GPT-6.1 Sol Ultrafast is the same model served in OpenAI's Ultrafast mode, up to 8x faster. It has a 1.05M token context window (922K input, 128K output), support for text and image inputs, and reasoning effort from low through max.

GPT OSS 120B Ultra is a speed-optimized serving variant of gpt-oss-120b, OpenAI's open-weight Mixture-of-Experts language model with 117B total and 5.1B active parameters. The base model takes text input and produces text output with a 128K-token context window, configurable reasoning effort and native tool use.

GPT-4.1 is OpenAI's non-reasoning model that excels at instruction following and tool calling, with broad knowledge across domains. It takes text and image input and produces text output, with a 1M-token context window, up to 32K output tokens and low latency without a reasoning step.

GPT-4.1 Mini is a smaller, faster version of OpenAI's GPT-4.1, built for instruction following and tool calling without a reasoning step. It takes text and image input and produces text output, with a 1M-token context window and up to 32K output tokens.

GPT-4.1 Nano is the fastest, most cost-efficient version of OpenAI's GPT-4.1, built for instruction following and tool calling without a reasoning step. It takes text and image input and produces text output, with a 1M-token context window and up to 32K output tokens.

GPT-5 is OpenAI's reasoning model for coding, reasoning and agentic tasks across domains, with configurable reasoning effort (minimal, low, medium and high). It takes text and image input and produces text output, with a 400K-token context window and up to 128K output tokens.

GPT-5 Mini is a faster, more cost-efficient version of OpenAI's GPT-5 reasoning model, suited to well-defined tasks, precise prompts and high-volume, low-latency workloads. It takes text and image input and produces text output, with a 400K-token context window and up to 128K output tokens.

GPT-5 Nano is the fastest, lowest-cost version of OpenAI's GPT-5 reasoning model, suited to summarization and classification tasks. It takes text and image input and produces text output, with a 400K-token context window and up to 128K output tokens.

GPT-5.1 is OpenAI's GPT-5 series model for coding and agentic tasks, with configurable reasoning effort that includes a non-reasoning setting. It takes text and image input and produces text output, with a 400K-token context window and up to 128K output tokens.

GPT-5.4 Nano is the lowest-cost GPT-5.4-class model from OpenAI, designed for simple, high-volume tasks where speed and cost matter most, such as classification and data extraction. It takes text and image input and produces text output, with a 400K-token context window and up to 128K output tokens.

GPT-5.6 Luna is OpenAI's GPT-5.6 model for cost-sensitive, high-volume workloads, roughly matching the nano tier of earlier GPT-5 families. It takes text and image input and produces text output, with a context window of about 1.05M tokens, up to 128K output tokens and reasoning effort from none to max.

o3 is OpenAI's well-rounded reasoning model for complex tasks across domains. It takes text and image input and produces text output, with a 200K-token context window and up to 100K output tokens.

o3-mini is OpenAI's small reasoning model, offering strong reasoning at the cost and latency targets of o1-mini. It takes text input and produces text output, with a 200K-token context window and up to 100K output tokens.

o4-mini is OpenAI's fast, cost-efficient reasoning model, optimized for efficient performance in coding and visual tasks. It takes text and image input and produces text output, with a 200K-token context window and up to 100K output tokens.

Free access to GPT OSS 120B on limited shared capacity. Anonymous route; account opt-in required.

Free access to GPT OSS 20B on limited shared capacity. Anonymous route; account opt-in required.

GPT Image 1.5 is OpenAI's image generation model that takes text and image input, with improved instruction following and prompt adherence over earlier GPT Image models. This variant generates images from a text prompt.

text-embedding-3-large is OpenAI's larger text embedding model for search, clustering, recommendations and classification. It accepts up to 8,192 input tokens and returns 3,072-dimensional embeddings by default, which can be shortened with the dimensions parameter to trade accuracy for storage.

text-embedding-3-small is OpenAI's smaller, more efficient text embedding model for search, clustering, recommendations and classification. It accepts up to 8,192 input tokens and returns 1,536-dimensional embeddings by default, which can be shortened with the dimensions parameter.