GPT-5.5 Pro
Extended-reasoning configuration for planning and hard debugging. Expensive per token, so reuse and batch discounts matter most here.
At a glance.
| Provider | OpenAI |
| Family | gpt-5 |
| Released | 2026-04 |
| License | Proprietary |
| Context window | 1.1M tokens |
| Max output | 128K tokens |
| Modalities | text, image, pdf |
| Tool calling | Yes |
| Reasoning mode | Yes |
| Caching | none |
| Batch discount | 50% off |
What reuse looks like here.
What you actually pay once caching works.
At a typical 55% prefix reuse, a million input tokens on GPT-5.5 Pro effectively costs $30.00 instead of $30.00 - blending to roughly $67.50 with a 25% output share. Background work drops a further 50% on the batch tier.
Estimate it for your workloadRoutes through these aliases:
Same OpenAI client, this model.
from openai import OpenAI
client = OpenAI(base_url="https://api.zumik.ai/v1", api_key="zk_live_...")
r = client.responses.create(
model="gpt-5-5-pro", # or an alias like reasoning.best
input="Draft a fix for the failing test.",
)
print(r.usage.input_tokens_cached) # confirm reuseHow GPT-5.5 Pro stacks up.
Other options for these workloads.
GPT-5.5 Pro, answered.
How much does GPT-5.5 Pro cost?
GPT-5.5 Pro is $30.00 per million input tokens and $180.00 per million output tokens through Zumik. Cache reads are $30.00 per million, a 0% discount on input.
What is GPT-5.5 Pro's context window?
GPT-5.5 Pro supports a 1.1M-token context window with up to 128K output tokens.
Does GPT-5.5 Pro support prompt caching?
Yes. OpenAI uses Automatic prefix caching caching. In the Zumik corpus, GPT-5.5 Pro shows a median cache capture of 90% on agent workloads.
Which Zumik aliases route to GPT-5.5 Pro?
GPT-5.5 Pro is a candidate for the reasoning.best alias, selected when it wins under current routing policy.
Run GPT-5.5 Pro with reuse measured.
Point an OpenAI client at Zumik and see exactly how much of this model's input you are reusing.