sora-2-hdSora 2 is the higher-quality version of OpenAI's Sora 2 text-to-video and audio generation model, designed to produce more realistic, controllable, and detailed AI-generated videos with synchronized audio and advanced world simulation capabilities. It builds on Sora 2's breakthrough in video realism and physics-aware generation, offering enhanced visual fidelity and extended features for creative and professional use. Early access has been available to ChatGPT Pro subscribers via sora.com, with wider availability expected after the invite/beta rollout.
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from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="sora-2-hd", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="sora-2-hd",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )modelmessagesmax_tokenstemperaturetop_pstreamtoolsreasoning_effortstream_optionsthinkingextra_bodyUse these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
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GPT-5.6 Luna Pro uses the same underlying model as GPT-5.6 Luna, but runs with reasoning.mode set to pro to deliver higher-quality responses on complex tasks. It is optimized for deeper reasoning, advanced coding, and multi-step agentic workflows, offering improved accuracy and solution quality while retaining the efficiency and scalability of the Luna tier.
GPT-5.6 Luna is the fast, cost-efficient model in OpenAI's GPT-5.6 series, optimized for high-volume, latency-sensitive workloads. It delivers capable reasoning at an affordable price point, making it ideal for chat applications, classification, and lightweight agentic workflows. Designed for scalable production deployments, GPT-5.6 Luna balances speed, cost, and reliability, providing efficient performance for real-time applications and large-scale automation tasks.
GPT-5.6 Terra Pro uses the same underlying model as GPT-5.6 Terra, but runs with reasoning.mode set to pro to deliver higher-quality responses on complex tasks. Optimized for deeper reasoning and greater reliability, it is well suited for advanced coding, multi-step reasoning, and agentic workflows where improved accuracy and solution quality are more important than maximizing speed or minimizing cost.
GPT-5.6 Terra is the balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is designed for everyday coding, reasoning, and agentic workflows, delivering strong performance while balancing capability and cost. Offering near-flagship quality at approximately half the cost of Sol, GPT-5.6 Terra is well suited for production applications that require reliable reasoning, software development, and scalable agent execution.
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GPT-5.4 is OpenAI's latest frontier model, unifying the GPT and Codex lines into a single system designed for both general intelligence and advanced software engineering workflows. It supports text and image inputs and features a 1M+ token context window (≈922K input, 128K output), enabling high-context reasoning, coding, and multimodal analysis within a single workflow. The model delivers improved performance in coding, document understanding, tool use, and instruction following, and is designed as a strong default for complex tasks. It can generate production-quality code, synthesize information across large datasets, and execute multi-step workflows with fewer iterations and greater token efficiency.
GPT-5 is OpenAI's most advanced model, built for complex, high-stakes tasks that require careful step-by-step reasoning and precise instruction following. It improves code quality, writing, and reliability, supports test-time routing and intent cues like “think hard,” and reduces hallucinations and sycophancy across demanding workloads.
GPT-5 Mini is a smaller, faster, lower-cost version of GPT-5 for lighter reasoning workloads. It retains GPT-5's instruction-following and safety tuning, and serves as the successor to o4-mini.
gpt-oss-20b is an open-weight, 21B-parameter OpenAI model released under Apache 2.0. It uses a Mixture-of-Experts design so only ~3.6B parameters run each step, enabling faster, lower-cost inference on consumer or single-GPU hardware. Trained in the Harmony format, it supports configurable reasoning depth, fine-tuning, function calling, tool use, and structured outputs.
Initialized observational baseline with no recorded failures