One stable API surface
Call GPT 4o Mini with an APIAny key and a documented request format. Keep your application integration stable while model versions and upstream routes evolve behind the gateway.
Text Generation
OpenAI
GPT 4o Mini API
OpenAI GPT 4o Mini is a fast, economical multimodal model for everyday assistants, classification, extraction, and high-volume customer-facing workloads.
24H Status Monitor
24h success rate: 100%
Model:
Price: 0.55 credits per 1K input tokens · ≈ $0.0003-$0.0006 · 0.83 credits per 1K output tokens · ≈ $0.0004-$0.0008High stability with detailed usage records on the APIAny platform.
gpt-4o-mini
62 (suggested: 2,000)
0.7
02
Sampling temperature. Lower is more deterministic.
1024
168192
USD estimate $0.0005-$0.001: highest recharge package uses $1 = 2,000 credits; entry package uses $1 = 1,000 credits.
Preview
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History
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Input
0.55 credits/1K
≈ $0.0003-$0.0006
Output
0.83 credits/1K
≈ $0.0004-$0.0008
Cache
0.03 credits/1K
≈ $0.000014-$0.000028
Context
-
Max output
-
Pricing
Model ID
Type
Quality
Price
gpt-4o-mini
Text Generation
Input tokens
0.55 credits per 1K input tokens · ≈ $0.0003-$0.0006
gpt-4o-mini
Text Generation
Cache read tokens
0.03 credits per 1K cached input tokens · ≈ $0.000014-$0.000028
gpt-4o-mini
Text Generation
Output tokens
0.83 credits per 1K output tokens · ≈ $0.0004-$0.0008
gpt-4o-mini
Text Generation
Minimum request
0.03 credits minimum · ≈ $0.000014-$0.000028
Model IDgpt-4o-mini
TypeText Generation
QualityInput tokens
Price0.55 credits per 1K input tokens · ≈ $0.0003-$0.0006
Model IDgpt-4o-mini
TypeText Generation
QualityCache read tokens
Price0.03 credits per 1K cached input tokens · ≈ $0.000014-$0.000028
Model IDgpt-4o-mini
TypeText Generation
QualityOutput tokens
Price0.83 credits per 1K output tokens · ≈ $0.0004-$0.0008
Model IDgpt-4o-mini
TypeText Generation
QualityMinimum request
Price0.03 credits minimum · ≈ $0.000014-$0.000028
Model overview
What is the GPT 4o Mini API?
OpenAI GPT 4o Mini is a fast, economical multimodal model for everyday assistants, classification, extraction, and high-volume customer-facing workloads.
Measure throughput, latency, review effort, and unit economics against the operating target this model supports.
APIAny exposes GPT 4o Mini through one documented API surface with live pricing, model status, request examples, and an on-page playground. Teams can evaluate the model here, then keep authentication, usage records, and production routing in the same platform.
Try GPT 4o Mini in the playground
APIAny advantages
Why use GPT 4o Mini through APIAny?
APIAny combines direct model access with the operational controls needed to move from evaluation to production without maintaining a separate integration for every provider.
Transparent usage and pricing
Review the live GPT 4o Mini pricing rules before a request, estimate credits in the playground, and inspect request-level usage records after the call completes.
Production routing controls
Use model status, channel health, retry policy, and usage logs to operate GPT 4o Mini as part of a production workflow instead of treating it as an isolated demo.
Use cases
What can you build with the GPT 4o Mini API?
These workflows show where GPT 4o Mini fits in a real product. Test the same inputs in the playground, compare the output with related models, and choose the route that meets your quality, latency, and budget requirements.
01
Customer support assistants
Use GPT 4o Mini for support classification, answer drafting, self-service guidance, and multilingual conversations. Combine retrieval and policy checks so responses stay grounded in current product information.
Try GPT 4o Mini in the playground
02
Classification and structured extraction
Turn messages and documents into labels, fields, or JSON with GPT 4o Mini. Define a strict output schema and validate results before automated downstream actions.
Try GPT 4o Mini in the playground
03
Multilingual assistants
Build assistants that understand and respond across languages with GPT 4o Mini. Test terminology, tone, locale-specific formatting, and policy behavior with representative conversations before launch.
Try GPT 4o Mini in the playground
Integration
How to integrate the GPT 4o Mini API
Move from a playground test to an authenticated production request in three steps. The page keeps the model identifier, request schema, pricing, and response examples together. Deploy with bounded inputs, observable task states, and clear escalation or fallback paths.
- 01
Create an API key
Sign in to APIAny, create a project API key, and assign only the model scope and budget controls your application needs.
- 02
Send a GPT 4o Mini request
Copy the request example from this page, set the model field to the selected GPT 4o Mini version, and send it to the documented APIAny endpoint.
- 03
Monitor and refine
Track status, latency, credits, and returned usage. Compare versions or related models with the same workload before shifting production traffic.
Core capabilities
Key GPT 4o Mini API features
The following capabilities explain the practical input, output, and workflow characteristics that matter when evaluating GPT 4o Mini. Available request parameters remain visible in the live API reference on this page.
/01
Multimodal understanding
Combine supported text and visual inputs so GPT 4o Mini can reason over more than one content format in the same workflow.
/02
Low-latency execution
Use the faster GPT 4o Mini route for interactive experiences, rapid iteration, and workloads where response time matters.
/03
Cost-efficient scaling
Run higher-volume GPT 4o Mini workloads while using live pricing and request-level usage records to control spend.
/04
Streaming responses
Render supported GPT 4o Mini text output incrementally for interactive assistants and long-running generation tasks.
/05
OpenAI-compatible integration
Use familiar request patterns where supported, while APIAny handles authentication, model selection, billing, and usage records.
FAQ
GPT 4o Mini API frequently asked questions
Direct answers about capabilities, use cases, integration, and choosing the right GPT 4o Mini route.
What is the GPT 4o Mini API?
OpenAI GPT 4o Mini is a fast, economical multimodal model for everyday assistants, classification, extraction, and high-volume customer-facing workloads. APIAny makes this model callable through an authenticated API with live pricing, status information, request examples, and a browser playground on the same page.
What can I build with the GPT 4o Mini API?
Common GPT 4o Mini workflows include Customer support assistants, Classification and structured extraction, Multilingual assistants. The best fit depends on the input format, output quality, latency, and cost your product requires.
How do I call GPT 4o Mini through APIAny?
Create an APIAny key, use the endpoint documented on this page, and set the request model field to the selected GPT 4o Mini version. The playground can generate a working payload before you integrate it into application code.
How should I choose a GPT 4o Mini version?
Compare the versions shown on this page by price, supported parameters, and capabilities such as Multimodal understanding, Low-latency execution, Cost-efficient scaling. Test a representative production input before choosing the default route.
API Reference
Call this model through a standard REST API. Authenticate with your API key, then pick an endpoint below to see its parameters and examples.
Authentication
Every request needs a Bearer token in the Authorization header. Create an API key in the console.
Authorization: Bearer YOUR_API_KEYPOST
https://apiany.ai/v1/chat/completionsRequest parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
model | string | Required | Model identifier to invoke. Use this model's ID. |
messages | array | Required | Conversation history in OpenAI chat format (role + content). |
stream | boolean | Optional | When true, the response streams back as server-sent events. |
Request example
curl "https://apiany.ai/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini",
"messages": [
{
"role": "user",
"content": "Summarize the following text in three concise bullet points:"
}
],
"temperature": 0.7,
"max_tokens": 1024
}'Response example
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"model": "gpt-4o-mini",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I help?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 12,
"completion_tokens": 18,
"total_tokens": 30
}
}
