
gpt-5.6-sol-pro
API Overview
GPT-5.6 Sol is the flagship, top-tier large model in OpenAI’s GPT-5.6 family, forming a new-generation product lineup alongside the mid-range Terra and the cost-effective Luna.
Sol is specifically designed for highly complex agent tasks, ultra-long-term workflows, and advanced logical reasoning, representing the current industry benchmark for large models in terms of “high intelligence and robust resilience.”
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Core Capabilities
Ultra-Level Multi-Agent Parallel Verification: An industry-leading native multi-agent parallel cross-validation mechanism. When facing extremely ambiguous or high-risk production tasks, Sol Pro can automatically split and orchestrate four independent agent pipelines internally, each responsible for path planning, code writing, sandbox testing, and security auditing. Through multi-perspective adversarial checks and cross-blind reviews, it completely eliminates logical gaps and hallucinations.
Extremely Resilient Long-Term Trajectory Planning: It sets a new industry benchmark in the notoriously challenging multi-step agent evaluation test, Agents' Last Exam (covering 55 specialized fields). The model boasts exceptionally strong autonomous retry capabilities. When encountering intermediate errors or obstacles in external tool calls, it does not stall or fall into infinite loops; instead, like a human expert, it proactively overturns incorrect assumptions, saves a snapshot of its current progress, and replans the optimal path.
ARC-AGI Abstract Logical Dimensionality Reduction: It perfectly inherits and enhances the groundbreaking performance demonstrated on the general artificial intelligence abstract reasoning test, ARC-AGI-3. It possesses exceptional cross-ecosystem generalization capabilities and can completely break free from reliance on specific prompt engineering. In entirely unfamiliar hardware instruction environments or unknown system topologies, Sol Pro can rapidly complete rule derivation and self-alignment with just a minimal number of exploration samples.
Pixel-Level Frontend UI Visual Self-Review: The system’s automated control capabilities have reached a qualitative leap. Not only can it efficiently write full-stack frontend code spanning multiple files, but it also features advanced “visual layout aesthetics and ergonomics self-review” capabilities. Before delivering results to users, the model will autonomously invoke the visual layer to conduct pixel-level reviews of the generated page rendering effects, proactively fixing visual defects or color breaks in dark mode.
Playground
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