GPT-5.6 Sol or GPT-5.6 Luna?
Choose GPT-5.6 Sol when professional api workflows where token cost and reasoning controls matter is the closer match. Choose GPT-5.6 Luna when high-volume extraction, classification and routine agent tasks matters more. Test both on the same real tasks before moving a production workflow.
Professional API workflows where token cost and reasoning controls matter
High-volume extraction, classification and routine agent tasks
GPT-5.6 Sol
Professional API workflows where token cost and reasoning controls matter
Official specification ↗GPT-5.6 Luna
GPT-5.6 model optimized for cost-sensitive, high-volume workloads.
Official specification ↗Side-by-side comparison
| Category | GPT-5.6 Sol | GPT-5.6 Luna |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Type | Product · Reasoning Model | Model · Reasoning model |
| Pricing summary | API / 1M tokens: $4 input, $0.40 cached input, $20 output; long-context/tool charges extra | $0.20 input, $0.02 cached input and $1.20 output per 1M tokens |
| Input price | Product or plan pricing | $0.20 / 1M tokens |
| Cached input | Not directly comparable | $0.02 / 1M tokens |
| Output price | Product or plan pricing | $1.20 / 1M tokens |
| Context window | Varies by included model and plan | 1.05M tokens |
| Maximum output | Varies by included model and surface | 128K tokens |
| Knowledge cutoff | Model-dependent; web access may add current information | February 16, 2026 |
| Reasoning | Varies by selected model or mode | none, low, medium, high, xhigh, max |
| Relative speed | Varies by model, plan and workload | Fast / cost optimized |
| Input modalities | See documented product features | Text and image |
| Output modalities | See documented product features | Text |
| Tools and integrations | 1.05M-token context; up to 128K output; Text/image input and text output; Reasoning effort includes none; gpt-5.6 alias routes to Sol | Functions, web search, file search, computer use and supported Responses API tools |
| API / access | Product surface; see official source for API availability | v1/responses, v1/chat/completions and v1/batch |
| Best fit | Professional API workflows where token cost and reasoning controls matter | High-volume extraction, classification and routine agent tasks |
| Company | OpenAI | OpenAI |
| Product category | Product · Reasoning Model | Model · Reasoning model |
| Current pricing note | API / 1M tokens: $4 input, $0.40 cached input, $20 output; long-context/tool charges extra | $0.20 input, $0.02 cached input and $1.20 output per 1M tokens |
| Best suited to | Professional API workflows where token cost and reasoning controls matter | High-volume extraction, classification and routine agent tasks |
| Key capabilities | 1.05M-token context; up to 128K output; Text/image input and text output; Reasoning effort includes none; gpt-5.6 alias routes to Sol | 1.05M context; 128K maximum output; Vision input; Responses API tools |
| Last verified | 2026-09-07 | 2026-09-08 |
| Official product source | https://developers.openai.com/api/docs/models/gpt-5.6-sol | https://developers.openai.com/api/docs/models/gpt-5.6-luna |
How we reached this verdict
We looked at the things that affect everyday use: what each product can do, how its plans are structured, where it fits into your existing workflow, and what the provider currently documents. Benchmark results are useful context, but they are not a universal winner score because test settings and tools vary.
Common questions
GPT-5.6 Sol or GPT-5.6 Luna: which should I choose?
Choose GPT-5.6 Sol for professional api workflows where token cost and reasoning controls matter. Choose GPT-5.6 Luna for high-volume extraction, classification and routine agent tasks. Validate the decision with your own prompts and total task cost.
Is GPT-5.6 Sol cheaper than GPT-5.6 Luna?
Pricing units can differ. GPT-5.6 Sol: API / 1M tokens: $4 input, $0.40 cached input, $20 output; long-context/tool charges extra. GPT-5.6 Luna: $0.20 input, $0.02 cached input and $1.20 output per 1M tokens. Check tool charges, plan limits, caching and long-context rules before comparing totals.
Which is better for coding and agent work?
Capability depends on the selected product surface, tools and harness. GPT-5.6 Sol is positioned for professional api workflows where token cost and reasoning controls matter; GPT-5.6 Luna is positioned for high-volume extraction, classification and routine agent tasks. Run the same repository task on both.
How do their context windows compare?
GPT-5.6 Sol lists Varies by included model and plan; GPT-5.6 Luna lists 1.05M tokens. A larger limit does not by itself guarantee better retrieval or lower cost.
Official sources
Use these provider pages to confirm current features, pricing and availability.
AI tools change quickly. We checked this page on 2026-09-08. Before you subscribe, confirm the latest price, regional availability and usage limits on the provider website.