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OpenAI introduced the GPT‑5.6 family on July 9, 2026, calling GPT‑5.6 Sol its most capable model yet. Sol is the flagship for difficult reasoning, coding, science, cybersecurity and agentic work; Terra targets a lower cost, while Luna is optimized for speed and high-volume workloads. The release followed a restricted preview that began June 26.
What OpenAI actually launched
GPT‑5.6 is a three-model family rather than a single upgrade. OpenAI says the number identifies the generation, while the names represent durable capability tiers that can advance independently. The family became available across ChatGPT, Codex and the API beginning July 9, with rollout continuing gradually over the following 24 hours.
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| Model | Positioning | Best fit | Main trade-off |
|---|---|---|---|
| GPT‑5.6 Sol | Highest-capability flagship | Complex coding, research, planning, cybersecurity and multi-step agents | Highest price and potentially greater latency |
| GPT‑5.6 Terra | Lower-cost, GPT‑5.5-level target | High-quality production work where economics matter | Lower ceiling on the hardest tasks |
| GPT‑5.6 Luna | Fastest and most cost-efficient tier | Classification, extraction, routing and routine generation at scale | Less suitable for difficult reasoning |
That structure matters commercially: many applications do not need Sol, and Terra or Luna can provide better total economics when the work is repetitive or latency-sensitive.
The Tool Desk
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“Most capable” is OpenAI’s positioning, not an independently settled verdict. The company says Sol improves long-horizon planning, command-line work, tool coordination, computer use, design judgment, scientific and biological reasoning, cybersecurity analysis, token efficiency and estimated cost per successful task.
OpenAI reports a score of 53.6 on Agents’ Last Exam, an evaluation of long-running professional workflows across 55 fields. It says Sol exceeded Claude Fable 5 with adaptive reasoning by 13.1 points; at medium reasoning, OpenAI reports an 11.4-point advantage at approximately one-quarter of the estimated cost. These are company-reported results under specified evaluation conditions, not proof that Sol wins every real-world job.
What is technically new
More reasoning controls
Sol adds a max reasoning effort and an ultra mode that uses multiple subagents in parallel for complex work. Deeper settings can increase latency, token use and cost. They are processing controls, not a guarantee of correctness.
Programmatic and multi-agent tool use
In the Responses API, GPT‑5.6 supports Programmatic Tool Calling, in-memory program execution for coordinating tools and intermediate results, and a multi-agent capability described initially as beta. Concurrent subagents can divide a task and then synthesize their work. OpenAI also says the programmatic tool-calling workflow can be compatible with Zero Data Retention when the relevant product configuration and policy requirements are met.
Context, output and tools
The API model documentation lists a 1.05-million-token context window, a 128,000-token maximum output, text and image input, text output, and tools including functions, web search, file search and computer use. Those API specifications should not automatically be assumed for every ChatGPT interface or plan. See the API model catalog.
What the reported evaluations show
Coding and terminal workflows
OpenAI says Sol achieved state-of-the-art performance on Terminal-Bench 2.1, which tests command-line planning, iteration and tool coordination. A benchmark result does not establish reliable behavior across every repository, operating system or production environment.
Professional knowledge work
Agents’ Last Exam measures selected long-running workflows, not every occupation or regulated process. Human review remains necessary where errors carry legal, financial, medical or operational consequences.
Cybersecurity
OpenAI describes Sol as its strongest cybersecurity model and reports competitive ExploitBench performance with another frontier system while using about one-third as many output tokens. “Competitive” is not universal superiority: results depend on the harness, prompts, tools, configuration and token budget, and may use controlled or simulated environments.
For legitimate defense, Sol may assist with vulnerability triage, code review and authorized testing. Keep work sandboxed, isolate credentials, control network egress, log every action and require human approval before any consequential change. This article does not provide exploitation instructions.
Biology and science
OpenAI reports gains on GeneBench and other biology evaluations, including long-horizon genomics and quantitative-biology analysis. Assistance with analysis is not autonomous scientific discovery or safe execution of laboratory procedures.
Availability checked August 18, 2026
Access differs by product, plan and rollout stage, and account labels can change.
- ChatGPT Work and Codex: Free and Go users receive Terra access. Plus, Pro, Business and Enterprise users can choose among Sol, Terra and Luna subject to product limits.
- Chat: Plus, Pro, Business and Enterprise users receive Sol through medium and higher effort settings; Pro and Enterprise users can access Sol Pro for the highest-quality complex-task results.
- Codex:
ultrais available to Plus and higher plans. - ChatGPT Work:
ultrais available to Pro and Enterprise users. - API: Developers can use Sol, Terra and Luna.
The June 26 preview was different: access initially went to a small group of trusted partners and organizations through the API and Codex at the U.S. government’s request. OpenAI described that approval path as temporary rather than a permanent requirement.
API prices after the July 30 update
The July 9 launch page listed higher initial Terra and Luna prices. The figures below are the later prices verified August 18, 2026.
| Model | Input per 1M tokens | Cached input | Output per 1M tokens |
|---|---|---|---|
| GPT‑5.6 Sol | $5.00 | $0.50 | $30.00 |
| GPT‑5.6 Terra | $2.00 | $0.20 | $12.00 |
| GPT‑5.6 Luna | $0.20 | $0.02 | $1.20 |
Terra and Luna received the reductions in OpenAI’s July 30 pricing update. Cached-input rates represent the stated 90% discount. Explicit cache breakpoints have a stated 30-minute minimum cache life; cache writes cost 1.25 times the uncached input rate. Savings depend on sending stable repeated context in a way the cache can use.
OpenAI also says Sol Fast can deliver up to 2.5 times standard processing speed at twice the price, without changing the model’s intelligence. Actual latency varies with demand, request size, tools, reasoning effort and service conditions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Safety and governance implications
The GPT‑5.6 preview system card classifies Sol, Terra and Luna as High capability for cybersecurity and biological/chemical risk under OpenAI’s Preparedness Framework.
OpenAI says it used human red-teaming, large-scale automated testing, real-time checks, monitoring, trust- and risk-calibrated access, additional protections for sensitive cyber requests and repeated misuse, and a rapid process for reproducing and fixing newly discovered jailbreaks. Those measures reduce risk but do not prove safety in every product configuration, multi-step attack or real-world workflow.
Agentic systems also create practical failure modes:
- Errors can cascade between subagents.
- Tools can be called incorrectly or repeatedly, creating runaway loops.
- Parallel workers can produce conflicting conclusions and higher bills.
- External tools can expose sensitive data or trigger irreversible actions.
- Long decision chains can be difficult to audit.
Start with read-only tools, impose time, token and spending limits, log calls and intermediate results, require confirmation for irreversible actions, and test recovery from failure separately from normal task success.
Which GPT‑5.6 model should you use?
| Workload | Starting choice | Reason |
|---|---|---|
| Complex coding, research, planning or multi-step professional work | Sol | Highest reported capability and broadest reasoning profile |
| High-quality production work with a strict budget | Terra | Balances capability and price |
| High-volume classification, extraction or routing | Luna | Lowest listed price and fastest positioning |
| Tool-heavy agents | Sol or Terra | Supports tool and programmatic coordination |
| Large repeated prompts or codebases | Any tier with caching | Stable context can reduce recurring input cost |
Choose by total cost, not token price alone: input tokens + output tokens + tool calls + retries + human review + infrastructure. A cheaper model that needs more retries or verification may cost more per successful task.
Practical access options
- ChatGPT is the simplest route for individuals who want a ready-made interface; plan entitlements are listed at ChatGPT.
- Codex suits engineers who want a managed coding-agent experience; see OpenAI Codex.
- API access is intended for products, automation and measurable usage-based deployment; consult the model documentation.
- Cerebras delivery was announced for select customers at up to 750 tokens per second, so it is a specialized low-latency option rather than ordinary public access. See Cerebras.
Limits readers should keep in mind
Benchmark leadership depends on prompting, reasoning settings, tools, attempts, token budgets and evaluation harnesses. Current events, live prices, changing libraries and account entitlements still require retrieval or other current tools. The API documentation lists a February 16, 2026 knowledge cutoff for Terra and Luna; that date should not be generalized to Sol without its corresponding model entry.
OpenAI’s launch announcement and preview announcement provide the company’s capability, access and safety claims.
Quick Recap
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