gpt-4-0613 API
gpt-4-0613 is a text-generation model from OpenAI. In ServerNet, its chat route accepts conversation messages and returns a generated answer; the price separates input and output tokens.
AvailableToman per million tokens
Prices exclude tax. The current Iran usage tax rate is 10%. The rate applicable to your account is fixed at request admission.
- API model ID
- gapgpt-gpt-4-0613-41a8859acd
- Model developer
- OpenAI
- Service type
- Text chat
- Current availability
- Available
- Configured context limit
- 4,096 tokens
- Gateway output cap
- 1,024 tokens
Model features
Streaming ✓
What is gpt-4-0613?
Use the public identifier gapgpt-gpt-4-0613-41a8859acd for gpt-4-0613 in ServerNet. The gateway uses this identifier to select the configured route; the developer is OpenAI.
For gpt-4-0613, use the listed model ID and endpoint instead of assuming every GPT parameter is supported. Compare both input and output prices for your expected request size.
Where to use gpt-4-0613
- Add gpt-4-0613 to a support assistant that receives the relevant conversation as text.
- Test gpt-4-0613 on summaries and extraction using your own documents, with a small output limit first.
- Compare answer quality, total token usage and cost per completed task before choosing gpt-4-0613 for production.
Build your integration
Send system and user messages, set max_tokens and store X-Request-Id with your usage record. Stream only when this route supports it. Function calls describe actions for your application to run; the gateway does not execute your tools.
Inputs and service limits
The current chat route accepts text only and one completion per request. Images, audio and hosted paid tools are not enabled by the source model’s capabilities. The configured context and output limits may be below the developer’s maximum. Test language quality on your own dataset.
A request cost example
For 1,000 input tokens and 500 output tokens, without a cache discount. This is a catalogue estimate, not a fixed request fee. Reported consumption, applicable tax and the price frozen for your request determine settlement.
- Usage before tax, Toman
- 16,790
- Tax (10%), Toman
- 1,679
- Estimated total, Toman
- 18,469
Connect to gpt-4-0613 API
Enable ai:chat on your key and ai:models:read to check availability. Set SERVERNET_API_KEY in your server environment. Change the idempotency key for each new request; keep it unchanged only for an identical retry.
curl https://servernet.cloud/v1/chat/completions \
-H "Authorization: Bearer $SERVERNET_API_KEY" \
-H 'Content-Type: application/json' \
-H 'Idempotency-Key: CHANGE_FOR_EACH_NEW_REQUEST' \
-d '{
"model": "gapgpt-gpt-4-0613-41a8859acd",
"messages": [
{
"role": "user",
"content": "Hello"
}
],
"max_tokens": 128
}'
Use the same Idempotency-Key when retrying an identical request. Successful responses are replayed without a second charge for 24 hours. Do not automatically retry when x-should-retry:false is present. The key is shown once. Store it in a server environment variable. Keep it out of browser code, GitHub and logs.
Keys, budgets and usage reportsFrequently asked questions
Is gpt-4-0613 available through ServerNet?
gpt-4-0613 is currently available on the configured route. Check GET /v1/models before sending a request: availability can change with provider capacity, catalogue freshness or account configuration.
Which model ID and API endpoint should I use for gpt-4-0613?
Use gapgpt-gpt-4-0613-41a8859acd as the model field, the endpoint shown below and the matching key scope. ServerNet keys are project-specific; an SDK also needs https://servernet.cloud/v1 as its base URL.
How is gpt-4-0613 usage charged?
Input and output tokens use separate tariffs. Reported reasoning tokens, where supported, count towards output consumption. Cached input receives a discount only when a verified cached tariff exists. Usage and applicable tax appear separately in the dashboard.
What should I check before using gpt-4-0613 in production?
The current chat route accepts text only and one completion per request. Images, audio and hosted paid tools are not enabled by the source model’s capabilities. The configured context and output limits may be below the developer’s maximum. Test language quality on your own dataset.
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