Endpoint coverage
Exposes 2 public endpoint(s): chat_completion, response.
curl -X POST https://runapi.ai/v1/chat/completions \
-H "Authorization: Bearer $RUNAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini",
"messages": [
{
"role": "user",
"content": "Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."
}
]
}'
import { GptClient } from "@runapi.ai/gpt";
const client = new GptClient();
const result = await client.chatCompletion.run({
model: "gpt-4o-mini",
messages: [{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}],
});
import os
import requests
response = requests.post(
"https://runapi.ai/v1/chat/completions",
headers={"Authorization": f"Bearer {os.environ['RUNAPI_API_KEY']}"},
json={"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]}
)
response.raise_for_status()
<?php
$client = curl_init("https://runapi.ai/v1/chat/completions");
curl_setopt_array($client, [
CURLOPT_HTTPHEADER => ["Authorization: Bearer " . getenv("RUNAPI_API_KEY"), "Content-Type: application/json"],
CURLOPT_POSTFIELDS => json_encode([
'model' => 'gpt-4o-mini',
'messages' => [['role' => 'user', 'content' => 'Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations.']],
])
]);
$response = curl_exec($client);
RunApi client = new RunApi(System.getenv("RUNAPI_API_KEY"));
Task task = client.chatCompletion().run({"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]});
task.waitForResult();
require "runapi/gpt"
client = RunApi::Gpt::Client.new
result = client.chat_completion.run(
model: "gpt-4o-mini",
messages: [{role: "user", content: "Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]
)
client := runapi.NewClient(os.Getenv("RUNAPI_API_KEY"))
task, err := client.chatCompletion.Run({"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]})
if err != nil { log.Fatal(err) }
task.Wait()
$ runapi generate \
--model gpt-4o-mini \
--endpoint chat_completion \
--wait
17 versions available
Pick any model and generate in seconds.
| Provider | OpenAI |
| Model ID | gpt-4o-mini |
| Modality | Text |
| Task types | Synchronous |
| API endpoint | /v1/chat/completions |
| /v1/responses |
| /v1/messages | |
| /v1beta/models/gpt-4o-mini:generateContent | |
| /v1beta/models/gpt-4o-mini:streamGenerateContent | |
| Billing unit | 1K tokens |
| Catalog status | Operational |
Sign up for free and create an API key for gpt-4o-mini from the dashboard.
POST to /v1/chat/completions with the gpt-4o-mini model slug and your parameters.
Read the completed gpt-4o-mini response directly from the endpoint.
Exposes 2 public endpoint(s): chat_completion, response.
Metered by 1K tokens with no subscription requirement.
No request parameters are published for this endpoint.
Answer customer questions from a private knowledge base, reducing ticket volume.
Draft contract summaries and flag key clauses for attorney review.
Auto-generate unit tests, code reviews, and refactoring suggestions in CI.
Verified customer feedback is not available for this model yet.
Pass the model ID shown in the quickstart.
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Yes. Variant is a parameter in the request. Switch by changing the model ID — no code changes, no re-authentication, no separate billing setup. All variants share the same API key and request shape.
Where streaming is available, RunAPI streams end-to-end. LLM models support token-level streaming. Media models use async task polling or webhook callbacks for result delivery.
Open an issue on the public GitHub repo or email support at [email protected]. Include the task ID and model ID so the team can investigate the specific generation.
No. Your RunAPI API key is enough to access this variant and every other model in the catalog. You do not need accounts with the underlying provider.
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