Compare
GPT-5.5 Pro vs GPT-5.6 Luna
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
GPT-5.5 Pro
Context window
1.1M
1,050,000 tokens · ~788K words
Model
GPT-5.6 Luna
Context window
1.1M
1,050,000 tokens · ~788K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Same context window size for both models.
GPT-5.5 Pro and GPT-5.6 Luna have identical context windows (1050K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | GPT-5.5 Pro | GPT-5.6 Luna |
|---|---|---|
| Context window | 1,050,000 tokens (1050K) | 1,050,000 tokens (1050K) |
| Max output tokens | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Speed tier | Balanced | Balanced |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | Apr 2026 | Jul 2026 |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | GPT-5.5 Pro in | GPT-5.5 Pro out | GPT-5.6 Luna in | GPT-5.6 Luna out |
|---|---|---|---|---|
| Openai | — | — | $1.00/M | $6.00/M |
Frequently asked questions
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Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
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