The balanced workhorse tier of GPT-5.6, combining capability and cost. Well suited to production work involving image understanding, tool use, and large source material; choose Sol for the hardest quality-first work or Luna for cost-controlled high volume.

The flagship GPT-5.6 tier for complex professional work and quality-first delivery. It supports image input, function calling, structured outputs, and an exceptionally large context window; consider Terra or Luna when latency or unit cost is the primary constraint.

The cost-sensitive, high-volume tier of GPT-5.6. A good fit for summarization, classification, rewriting, and batch automation; choose the Sol sibling for complex professional judgment or quality-first multi-step work.

A frontier reasoning model for coding, knowledge work, and STEM tasks. It supports image input, function calling, and structured outputs; its 500K-token context suits cross-file analysis and long source material. Prefer a lower-cost model when frontier reasoning is unnecessary.

Anthropic's most capable widely released model, built for the most demanding reasoning and long-horizon agentic work. Offers a 1M-token context window with 128k max output and always-on adaptive thinking, excelling at autonomously exploring underspecified tasks, planning, and carrying long-running coding and multi-agent orchestration further before it needs human input.

A daily-driver Sonnet-tier model aimed at bringing near-frontier agentic, coding, and knowledge-work capability at a lower operating cost. Its default 1M-token context and adaptive thinking fit long documents, codebases, and multi-step tool workflows; for the deepest reasoning or restricted high-risk security work, evaluate higher-tier or specialized models.

A LongCat 2.0 workhorse for project-scale coding and long-running agent tasks, with native 1M-token context plus tool calling and multi-step reasoning. It is best when you need to keep large repositories, long documents, or automation workflows in scope; for lightweight Q&A or low-latency chat, a smaller Flash/Lite-style model is usually cheaper.

Built for coding, agents, and complex productivity tasks, advancing beyond Doubao Seed 2.0 in long context, long output, and tool-oriented workflows. Compared with Qwen, GLM, and DeepSeek peers, it is a cost-effective option for Chinese office work, coding, and multi-step automation.

Built for text-to-video, with a stronger audio-native workflow than HappyHorse 1.0, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for reference-to-video, with a stronger audio-native workflow than HappyHorse 1.0, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.