OpenAI API
The most widely used LLM API. Powers GPT-4o and o1 models with best-in-class reasoning, vision, and structured outputs. Largest ecosystem of tutorials, integrations, and community support.
Why OpenAI API?
You need the most capable general-purpose model
Your use case requires vision or structured JSON outputs
You want the largest ecosystem of tutorials and integrations
Signal Breakdown
What drives the Trust Score
Download Trend
Last 12 months
Tradeoffs & Caveats
Know before you commitCost is a primary constraint (Groq is ~10× cheaper for speed)
You need guaranteed EU data residency
Latency is critical and you can tolerate lower quality
Pricing
Free tier & paid plans
No free tier
$0.002/1K tokens (GPT-3.5) · $0.01/1K (GPT-4o)
Pay-per-use, no subscription
Cost Calculator
Estimate your OpenAI API cost
Estimated monthly cost
$10 – $60/mo
GPT-3.5: ~$0.002/1K · GPT-4o: ~$0.01/1K · GPT-4: ~$0.03/1K
Estimates only. Verify with official pricing pages before budgeting.
Alternative Tools
Other options worth considering
Often Used Together
Complementary tools that pair well with OpenAI API
Learning Resources
Docs, videos, tutorials, and courses
Get Started
Repository and installation options
View on GitHub
github.com/openai/openai-node
npm install openaipip install openaiQuick Start
Copy and adapt to get going fast
import OpenAI from 'openai';
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const response = await client.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0].message.content);Code Examples
Common usage patterns
Streaming responses
Stream tokens as they are generated for a faster UX
import OpenAI from 'openai';
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const stream = await client.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Tell me a story.' }],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? '');
}Structured JSON output
Force the model to return a typed JSON object
import OpenAI from 'openai';
import { z } from 'zod';
import { zodResponseFormat } from 'openai/helpers/zod';
const ToolSchema = z.object({
name: z.string(),
category: z.string(),
trustScore: z.number(),
});
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const result = await client.beta.chat.completions.parse({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Describe Supabase as a tool.' }],
response_format: zodResponseFormat(ToolSchema, 'tool'),
});
console.log(result.choices[0].message.parsed);Function / tool calling
Let the model call your functions
const response = await client.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'What is the weather in NYC?' }],
tools: [{
type: 'function',
function: {
name: 'get_weather',
parameters: {
type: 'object',
properties: { location: { type: 'string' } },
required: ['location'],
},
},
}],
tool_choice: 'auto',
});
const call = response.choices[0].message.tool_calls?.[0];
if (call) {
const args = JSON.parse(call.function.arguments);
const weather = await getWeather(args.location);
}Community Notes
Real experiences from developers who've used this tool