Guide
GPT-5.4 API: Complete Developer Guide 2026
April 17, 2026 · 8 min read
GPT-5.4 is OpenAI's latest flagship model in 2026. It brings significant improvements in reasoning, instruction following, and function calling over GPT-4o. But at $3.75/$22.50 per million tokens, knowing when to use it and when to save money with alternatives is critical for any developer.
GPT-5.4 Key Capabilities
| Feature | GPT-5.4 | GPT-4o (previous) |
|---|---|---|
| Context window | 128K tokens | 128K tokens |
| Input cost (AIPower) | $3.75/M | $3.75/M |
| Output cost (AIPower) | $22.50/M | $22.50/M |
| Function calling | Advanced (parallel) | Standard |
| Structured output | JSON mode + schema | JSON mode |
| Knowledge cutoff | Early 2026 | Late 2024 |
Getting Started with GPT-5.4
from openai import OpenAI
client = OpenAI(
base_url="https://api.aipower.me/v1",
api_key="YOUR_AIPOWER_KEY",
)
response = client.chat.completions.create(
model="openai/gpt-5.4",
messages=[
{"role": "system", "content": "You are a senior software architect."},
{"role": "user", "content": "Design a rate limiter for a distributed system."},
],
temperature=0.7,
)
print(response.choices[0].message.content)Function Calling with GPT-5.4
GPT-5.4's improved function calling supports parallel tool execution and more reliable structured arguments:
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
},
"required": ["location"],
},
},
}
]
response = client.chat.completions.create(
model="openai/gpt-5.4",
messages=[{"role": "user", "content": "What's the weather in Tokyo and Paris?"}],
tools=tools,
tool_choice="auto",
)
# GPT-5.4 can call multiple tools in parallel
for tool_call in response.choices[0].message.tool_calls:
print(f"Function: {tool_call.function.name}")
print(f"Args: {tool_call.function.arguments}")Structured JSON Output
response = client.chat.completions.create(
model="openai/gpt-5.4",
messages=[{
"role": "user",
"content": "Extract key info from: Apple reported $94.9B revenue in Q1 2026, up 8% YoY."
}],
response_format={"type": "json_object"},
)
# Returns: {"company": "Apple", "revenue": "$94.9B", "period": "Q1 2026", "growth": "8%"}When to Use GPT-5.4 vs Cheaper Alternatives
| Use Case | GPT-5.4 ($3.75/M) | Better Alternative | Savings |
|---|---|---|---|
| Simple Q&A | Overkill | DeepSeek V3 ($0.34/M) | 91% |
| Classification | Overkill | GLM-4 Flash ($0.01/M) | 99% |
| Code generation | Good | Claude Sonnet 4 ($4.50/M) | Better quality |
| Function calling | Best | DeepSeek V3 ($0.34/M) | 91% (adequate) |
| Creative writing | Excellent | Claude Opus ($7.50/M) | Better quality |
| Latest knowledge | Best | No good alternative | Use GPT-5.4 |
Node.js Example
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.aipower.me/v1",
apiKey: "YOUR_AIPOWER_KEY",
});
const response = await client.chat.completions.create({
model: "openai/gpt-5.4",
messages: [{ role: "user", content: "Explain microservices vs monolith" }],
stream: true,
});
for await (const chunk of response) {
process.stdout.write(chunk.choices[0]?.delta?.content || "");
}Cost Optimization Strategy
Use GPT-5.4 strategically: route simple requests to cheaper models and reserve GPT-5.4 for tasks that truly benefit from it.
# Smart routing — let AIPower auto-select
response = client.chat.completions.create(
model="auto", # Routes to best model per task (often NOT GPT-5.4)
messages=[{"role": "user", "content": prompt}],
)
# Simple queries → DeepSeek V3, Complex → GPT-5.4 or ClaudeAccess GPT-5.4 and 15 other models at aipower.me — 50 free API calls, one API key for everything.