# GPT-5.5 vs GPT-5.6

As of November 10, 2026, GPT-5.5 costs 25% more per input token than GPT-5.6 ($5.00 vs $4.00 per 1M) and has a 1M-token context window versus 922K.

- Page: https://models.litellm.ai/compare/gpt-5.5-vs-gpt-5.6
- GPT-5.5: https://models.litellm.ai/models/gpt-5.5
- GPT-5.6: https://models.litellm.ai/models/gpt-5.6

## Side by side

| | GPT-5.5 | GPT-5.6 |
|---|---|---|
| Input, per 1M tokens | $5.00 | $4.00 |
| Output, per 1M tokens | $30.00 | $20.00 |
| Cache read, per 1M tokens | $0.50 | $0.40 |
| Cache write, per 1M tokens | – | $5.00 |
| Context window | 1,050,000 tokens | 922,000 tokens |
| Max output | 128,000 tokens | 128,000 tokens |
| Image input | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output (JSON) | Yes | Yes |
| Prompt caching | Yes | Yes |
| Reasoning | Yes | Yes |
| Providers on LiteLLM | 11 | 2 |
| Price shown is from | OpenAI | OpenAI |
| Added to LiteLLM | April 2026 | July 9, 2026 |

Headline prices in USD per 1M tokens, from LiteLLM's model price file.

## Cheapest provider for each

- GPT-5.5: OpenAI at $5.00 input per 1M tokens (`gpt-5.5`)
- GPT-5.6: OpenAI at $4.00 input per 1M tokens (`gpt-5.6`)

## When to pick which

- GPT-5.5: Larger context window: 1,050,000 vs 922,000 tokens.
- GPT-5.5: Available from 11 providers through LiteLLM, vs 2.
- GPT-5.6: Costs 20% less per input token: $4.00 vs $5.00 per 1M.

## FAQ

### Which is cheaper, GPT-5.5 or GPT-5.6?

GPT-5.6 is cheaper at 3 input tokens per output token: $8.00 per 1M tokens blended ($4.00 input, $20.00 output), versus $11.25 ($5.00 and $30.00) for GPT-5.5, as of November 10, 2026.

### Which has the larger context window, GPT-5.5 or GPT-5.6?

GPT-5.5 has the larger context window: 1,050,000 tokens, versus 922,000 for GPT-5.6.

### Can I switch from GPT-5.5 to GPT-5.6 without changing my code?

Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "gpt-5.5" to "gpt-5.6", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.