GPT-5.5 Pro is OpenAI's most advanced reasoning model of its generation, applying additional compute to GPT-5.5 to produce smarter and more precise responses on the hardest problems.
- Input
- text image $30/M
- Output
- text $180/M
- Context
- 1.1M
- Knowledge cutoff
- 2025-12
Benchmarks
Vendor-published: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai
Price in context
Where the price sits among 60 comparable models
The bar shows how this model’s price compares with every other model of the same kind on Synthorai. The cheapest and the most expensive are named at each end. These are base rates; batch, region and cache-write discounts are on the pricing page.
Specs & limits
Tokens
| Context window (vendor spec) | 1,050,000 |
|---|---|
| Max output (vendor spec) | 128,000 |
| Knowledge cutoff | 2025-12 |
Thinking
| Vendor control | reasoning.effort |
|---|---|
| Accepted values | medium · high · xhigh |
| Default | high applied when the request sets nothing |
| Can be turned off | No |
| Thinking behaviour | Responses API (including Batch) only; requests may take several minutes, so OpenAI recommends background mode. |
| Parameter | reasoning_effort |
| Values | minimal · low · medium · high the gateway's parameter surface - the vendor mapping above applies |
Model
| Modalities | text + image → text |
|---|
- Streaming not supported
- cached-input pricing discounts do not apply
- requests may take minutes (background mode recommended)
- reasoning effort medium-xhigh
Use GPT-5.5 Pro in 30 seconds
OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/chat/completions
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.chat.completions.create(
model="gpt-5.5-pro",
messages=[{"role": "user", "content": "Summarize this diff"}],
reasoning_effort="medium",
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://synthorai.io/v1",
apiKey: "sk-syn-...",
});
const resp = await client.chat.completions.create({
model: "gpt-5.5-pro",
messages: [{ role: "user", content: "Summarize this diff" }],
reasoning_effort: "medium",
});
console.log(resp.choices[0].message.content);curl https://synthorai.io/v1/chat/completions \
-H "Authorization: Bearer sk-syn-..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.5-pro",
"messages": [{"role": "user", "content": "Hello"}],
"reasoning_effort": "medium"
}'package main
import (
"context"
"fmt"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://synthorai.io/v1"),
option.WithAPIKey("sk-syn-..."),
)
resp, _ := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Model: "gpt-5.5-pro",
Messages: []openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Summarize this diff"),
},
ReasoningEffort: openai.ReasoningEffortMedium,
})
fmt.Println(resp.Choices[0].Message.Content)
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.*;
import com.openai.models.ReasoningEffort;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
ChatCompletion resp = client.chat().completions().create(
ChatCompletionCreateParams.builder()
.model("gpt-5.5-pro")
.addUserMessage("Summarize this diff")
.reasoningEffort(ReasoningEffort.MEDIUM)
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));About GPT-5.5 Pro
- It offers a 1,050,000-token context window (vendor spec), 128K max output tokens, image input, and reasoning effort at medium, high, and xhigh, with access to hosted tools such as web search, file search, and code interpreter.
- Effort defaults to high here, a step above GPT-5.4 Pro's medium default, so the expensive path is the one you get by default.
- Because responses can take minutes, OpenAI recommends background mode for long jobs.
- Two economics notes matter: the model offers no cached-input discount at all, so prompt reuse does not pay for itself the way it does elsewhere in the family, and its per-token rates sit several times above standard GPT-5.5.
- Unlike GPT-5.4 Pro it is available through the Batch API, which makes overnight bulk reasoning practical, but Chat Completions remains unsupported upstream, with the Responses API as the documented surface.
- Structured outputs, function calling, image input, hosted shell, and MCP are supported, and the knowledge cutoff is December 2025.
- On Synthorai, GPT-5.5 Pro sits behind the same OpenAI-compatible API as the rest of the fleet.
FAQ
Is the GPT-5.5 Pro API free to try?
Yes: new accounts get 10 trial calls and up to $1 in free credit, no card required. At $30/M input tokens, that credit alone covers roughly 4 requests of ~8K tokens against GPT-5.5 Pro.
What is GPT-5.5 Pro best at?
Additional compute for smarter, more precise responses; web search, file search, and code interpreter; background mode recommended for long jobs. See the About section for the full picture from the vendor's own release notes.
How much does GPT-5.5 Pro cost?
GPT-5.5 Pro costs $30 per million input tokens and $180 per million output tokens on Synthorai. That is the provider's list price, with no platform markup.
Does GPT-5.5 Pro support prompt caching?
GPT-5.5 Pro has no cache-read discount on Synthorai today. Prompt caching still applies to other models on the gateway; see the pricing table for cache-enabled alternatives. Provider caching comparison →
How do I get access to GPT-5.5 Pro?
Point your existing OpenAI SDK at base_url="https://synthorai.io/v1", set model="gpt-5.5-pro", and you're done. One API key covers every model on the gateway.
What is GPT-5.5 Pro's knowledge cutoff?
GPT-5.5 Pro's knowledge cutoff is 2025-12, per the vendor's official documentation (as of 2026-07-09).
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Every value on this page is transcribed from the vendor's own documentation, linked above, and carries the date it was checked. Prices are compared across the catalogue; specification values that vendors define differently are shown with the difference stated rather than charted. Nothing here is measured by us, and nothing is scored.