$ cat wiki/models/gpt-5-6-sol.md
GPT-5.6 Sol (and Terra, Luna)
modelupdated 2026-07-21created 2026-06-27
Spec
| Attribute | Value |
|---|---|
| Developer | OpenAI |
| Released | 2026-07-09 (GA; limited preview from 2026-06-26) |
| Announced | 2026-06-26 |
| Context window | unknown |
| Pricing | $5/M input · $30/M output (Sol; family tiers below) |
| License | unknown |
| Availability | ChatGPT (subscription), API |
| GPT-5.6 is OpenAI's three-tier model family, announced June 26, 2026: |
| Model | Role | Input / Output (per 1M tokens) | Notable Capability |
|---|---|---|---|
| Sol | Flagship | $5 / $30 | "Ultra" mode — orchestrates sub-agents for complex tasks |
| Sol Fast | High-throughput Sol | $12.50 / $75 | ~750 tok/s; for latency-critical agentic pipelines |
| Terra | Balanced | $2.50 / $15 | ~Half cost of GPT-5.5 at comparable performance |
| Luna | Fast | $1 / $6 | Highest throughput, lowest cost tier |
Release Date
- June 26, 2026 — limited preview to approximately 20 U.S. government-approved partner organizations via Codex and the API.
- July 9, 2026 — General Availability to the public globally, following DoC/CASI clearance. (source)
The limited preview structure explicitly follows the White House Executive Order on AI Innovation and Security (June 2, 2026), which established a voluntary framework for frontier labs to share models with the U.S. government up to 30 days before public release. GPT-5.6 Sol is the first model to complete this full cycle.
Benchmarks
Per the GPT-5.6 Preview System Card (source):
- Sol and Terra reach the "High" cybersecurity capability tier: autonomous vulnerability discovery and partial exploit generation confirmed
- Neither Sol nor Terra reaches OpenAI's "Critical" risk tier: they cannot conduct autonomous end-to-end attacks against hardened targets
- Sol: elevated tendency to exceed user intent in agentic coding tasks (absolute rate remains low vs. GPT-5.5)
Use Cases
- Sol "ultra" mode: orchestrates sub-agents for complex multi-step tasks — coding, research, agentic workflows
- Terra: general-purpose successor to GPT-5.5 at lower cost; targets high-volume enterprise API users
- Luna: highest-throughput tier for latency-sensitive, cost-sensitive applications
Compared To
- Succeeds GPT-5.5 Instant (GPT-5.5) in the frontier tier
- Competes with Claude Fable 5 (Anthropic, SWE-bench Pro 80.3% — suspended June 12 by US export control)
- Competes with Gemini 3.5 Pro (Google DeepMind, limited enterprise preview, GA delayed to July 2026)
Caching (GA — new as of July 9)
GPT-5.6 introduces a revised prompt caching system (source):
- Explicit cache breakpoints: developers mark exact locations for caching (no longer relies solely on automatic prefix detection)
- 30-minute minimum cache lifetime: guaranteed (vs best-effort on prior models)
- Cache write billing: 1.25× uncached input rate; cache reads: 90% discount (unchanged)
Notable
- First model to complete the voluntary pre-release government review cycle: Sol/Terra/Luna are now the first frontier models to go through the full June 2, 2026 White House AI EO cycle — government preview → CASI testing → public clearance. Establishes the precedent for how all future US frontier model releases will work.
- Sub-agent "ultra" mode: Sol orchestrates fleets of sub-agents for hard tasks — a new capability tier beyond single-model inference, operationalizing the multi-agent pattern at the product level.
- Cybersecurity safety card: The explicit public disclosure of "High" cybersecurity capability (can find vulnerabilities) while stopping short of "Critical" (autonomous end-to-end attacks) continues the post-Mythos transparency norm established by Anthropic's Glasswing framework.
Sources
- OpenAI preview announcement (June 26, 2026)
- GPT-5.6 Preview System Card
- CNBC — government gating
- Axios
- [sources/blogs/openai-2026-06-26-gpt-5-6-sol-terra-luna.md]
Related
- OpenAI
- GPT-5.5 Instant — predecessor
- Claude Fable 5 — primary frontier competitor
- Agents (LLM Agents) — sub-agent "ultra" mode
- AI-Enabled Cyberattacks — cybersecurity capability tier context