GPT-5.6 Sol

GPT-5.6 Sol is OpenAI's frontier flagship in the GPT-5.6 family, launched July 9, 2026. It sits at the top of a new three-tier naming system: Sol for frontier intelligence, Terra as a balanced daily driver, and Luna as the fast, affordable option. Sol brings a 1,050,000-token context window, reasoning effort up to a new max level, and an ultra mode that spins up subagents to accelerate complex work. OpenAI positions it as its strongest model yet for coding, biology workflows, cybersecurity, computer use, and design, and the model now ships at up to 750 tokens per second on Cerebras.

See also the previous snapshot GPT-5.2.

Core Features

• 1,050,000-token context: A 1.05M context window with up to 128,000 output tokens, designed for whole-repository and multi-system work.
• Six reasoning efforts: none, low, medium (default), high, xhigh, and new max for the deepest deliberation.
• Ultra mode: Goes beyond a single agent by leveraging subagents to parallelize complex work.
• Frontier agentic performance: New state of the art on Terminal Bench 2.1 for command-line, planning, and tool-coordination workflows.
• Cyber capability: Competitive with Claude Mythos Preview on ExploitBench while using roughly one-third of the output tokens.

Model Specifications

Pricing

Prompts with more than 272K input tokens are billed at 2x input and 1.5x output for the full request. Family pricing: Terra is $2.50/$15 and Luna is $1/$6 per 1M tokens.

Benchmark Highlights

• Terminal Bench 2.1: New state of the art on command-line workflows requiring planning, iteration, and tool coordination.
• GeneBench v1: Stronger results than GPT-5.5 on long-horizon genomics and quantitative-biology analysis, with fewer tokens.
• ExploitBench: Competitive with Mythos Preview at about one-third of the output tokens.
• ExploitGym: Strong improvements in cyber capabilities as reasoning effort increases.

Use Cases

• Complex professional work: Deep research, analysis, and deliverables that need sustained reasoning over long contexts.
• Agentic coding: Repository-scale implementations and multi-tool automation, including Codex integration.
• Cybersecurity and science: Long-horizon security research and biology workflows where the frontier tier matters.
• Cost-tiered scaling: Teams that want one API family with Sol, Terra, and Luna to match intelligence to budget.

Advantages

1. Reasoning depth: max effort plus ultra subagent mode offers deliberation beyond what GPT-5.5 exposed.
2. Huge context with caching: 1.05M context and 30-minute minimum cache life make long sessions economical.
3. Speed option: Up to 750 tokens per second on Cerebras brings frontier intelligence to latency-sensitive workflows.

Tips

1. Match effort to task: Use max and ultra only for genuinely hard, long-running work; lower efforts save significant cost on routine tasks.
2. Mind the long-context surcharge: Inputs over 272K tokens trigger 2x pricing, so compress or cache large prefixes.
3. Use explicit cache breakpoints: GPT-5.6's predictable caching rewards structuring prompts for reuse.

Conclusion

GPT-5.6 Sol is OpenAI's most capable general model, defined by deep reasoning controls, a massive context window, and frontier agentic and cyber benchmarks. Teams needing top-tier intelligence for the hardest work, with the option to scale down to Terra or Luna, should evaluate Sol first.

Alternatives

• Claude Fable 5: Anthropic's Mythos-class flagship with a similar 1M context and frontier coding.
• GLM-5.3: Open-weight coding leader with far lower per-token cost.
• Kimi K3: Open-weight 2.8T model with comparable agentic scores at much lower API prices.