OpenAI · Text chat

gpt-5.3-codex-spark API

gpt-5.3-codex-spark 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.

Preparing

Toman per million tokens

Input488,959
Output3,911,670

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-53-codex-spark-aa0caa1cd9
Model developer
OpenAI
Service type
Text chat
Current availability
Preparing
Configured context limit
4,096 tokens
Gateway output cap
1,024 tokens

Model features

Streaming ✓

What is gpt-5.3-codex-spark?

Use the public identifier gapgpt-gpt-53-codex-spark-aa0caa1cd9 for gpt-5.3-codex-spark in ServerNet. The gateway uses this identifier to select the configured route; the developer is OpenAI.

For gpt-5.3-codex-spark, measure whether the generated code passes your project tests. A plausible explanation alone does not verify program behaviour.

Where to use gpt-5.3-codex-spark

  • Add gpt-5.3-codex-spark to a support assistant that receives the relevant conversation as text.
  • Test gpt-5.3-codex-spark 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-5.3-codex-spark 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
2,445
Tax (10%), Toman
245
Estimated total, Toman
2,690

Connect to gpt-5.3-codex-spark 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.

This example documents the request format. Send it only after this model appears in GET /v1/models.

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-53-codex-spark-aa0caa1cd9",
    "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 reports

Frequently asked questions

Is gpt-5.3-codex-spark available through ServerNet?

gpt-5.3-codex-spark is currently unavailable for API use. A catalogue listing does not activate billing or access. Choose an available related model or check this page again after the route is verified.

Which model ID and API endpoint should I use for gpt-5.3-codex-spark?

Use gapgpt-gpt-53-codex-spark-aa0caa1cd9 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-5.3-codex-spark 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-5.3-codex-spark 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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Only available models are exposed by the API. Availability requires a configured provider, valid prices and a supported execution path.