GPT-5.6 Context Assurance

Use Entroly with GPT-5.6 Sol, Terra, and Luna.

Entroly recognizes the complete GPT-5.6 family and applies the correct context window, output reserve, reasoning metadata, and published list prices when planning context and reporting observable provider-bound cost.

Direct answer: Entroly supports gpt-5.6-sol, gpt-5.6-terra, and gpt-5.6-luna. It can reduce avoidable input tokens before supported API requests without blindly trimming answer-critical evidence. Savings vary by workload and are never guaranteed as one universal percentage.

Verified model metadata

ModelModel IDContextMax outputInput / output per 1M tokens
GPT-5.6 Solgpt-5.6-sol1,050,000128,000$5 / $30
GPT-5.6 Terragpt-5.6-terra1,050,000128,000$2.50 / $15
GPT-5.6 Lunagpt-5.6-luna1,050,000128,000$1 / $6

The unsuffixed gpt-5.6 alias resolves to Sol. All three support reasoning levels none, low, medium, high, xhigh, and max.

How Entroly lowers avoidable input cost

available repository and session evidence
                ↓
select answer-relevant evidence under a budget
                ↓
keep exact omitted originals content-addressable
                ↓
emit a Context Receipt of included and omitted evidence
                ↓
send the smaller provider-bound request to Sol, Terra, or Luna

Entroly measures provider-observed input reduction only on routes where the request is visible. SDK, MCP, or local-only reductions are reported separately and do not invent a dollar claim.

Choose the model tier independently from context assurance

Entroly preserves the same receipt, recovery, verification, and accounting contract across all three tiers, so switching models does not require redesigning context governance.

Quick start

pip install -U entroly
entroly verify-claims
entroly simulate
entroly proxy

Point a supported OpenAI-compatible application at the Entroly proxy, or use the SDK, MCP, wrapper, or native integration appropriate for your developer tool.

Important: Provider pricing, cache rules, availability, and model behavior can change. Entroly's registry stores provenance and verification dates, but production deployments should verify current OpenAI documentation before relying on cost estimates.

Official model sources