OpenAI GPT Mini Latest
OpenAI GPT Mini Latest is a lightweight, cost‑efficient GPT model from OpenAI optimized for fast, general-purpose language tasks.
What is OpenAI GPT Mini Latest?
OpenAI GPT Mini Latest is a compact generative AI language model designed by OpenAI for efficient text understanding and generation. It is commonly used for everyday chatbots, simple content drafting, and small-scale data transformation tasks. It also suits scenarios that require low latency and low cost, such as rapid prototyping or applications running at high request volumes. It belongs to the GPT family of OpenAI models, representing a smaller, more efficient tier compared with flagship GPT versions.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
| Provider | Input | Output | Cache read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| OpenAI | ~$0.08 | ~$0.08 | — | ~220ms | ~60 tps | 99.06% |
| Azure OpenAI | ~$0.09 | ~$0.09 | — | ~250ms | ~55 tps | 100.00% |
| Amazon Bedrock (GPT-equivalent mini) | ~$0.10 | ~$0.10 | — | ~260ms | ~50 tps | 99.9% |
Try this model
Test OpenAI GPT Mini Latest right here — free to start.
Suggestions for your first prompt
Code snippet
Call the model through the OpenAI-compatible API.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://inference.example.com/v1"
)
response = client.chat.completions.create(
model="openai/openai-gpt-mini-latest",
messages=[
{
"role": "user",
"content": "Describe this image in one sentence."
}
],
)
print(response.to_json())
{
"model": "openai/openai-gpt-mini-latest",
"messages": [
{
"role": "user",
"content": "Describe this image in one sentence."
}
]
}
Uptime
Last 30 days
28/30 days operational | 99.06% uptime
5 Core Capabilities
-
Conversational Chat
Handles interactive dialogue, answers questions, and follows instructions for everyday assistance, learning support, and simple task automation.
-
Image Interpretation
Accepts image inputs to identify objects, read visual context, and answer questions about pictures, diagrams, or simple screenshots.
-
Text Translation
Translates written text between multiple major languages, preserving core meaning and tone for short messages and simple documents.
-
Basic OCR
Extracts short, clear text from images such as signs, labels, or screenshots for use in answers or follow-up processing.
-
Content Monitoring
Supports lightweight content and safety checks, helping flag potentially unsafe, offensive, or disallowed text in user-provided content.
6 Most Valuable Use Cases
- Customer Support Chatbots
- High-Volume Text Summaries
- Code Generation Assistant
- Knowledge Base Search
- Usage Cost Optimization
- Log & Alert Monitoring
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Adaptive AI Routing
Dynamically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.
One endpoint, any model -
Cost-Aware Orchestration
Automatically pick the most cost-efficient model tier per request and track spend across vendors, so you stay within budget while maintaining performance.
Optimize cost per call -
Automatic Fallback Flows
Survive provider outages and model errors with policy-based failover that transparently retries on alternate models, keeping your production apps resilient.
Resilience by default -
End-to-End Observability
Get full visibility into prompts, latencies, errors, and model choices across providers with centralized logs and metrics for debugging and optimization.
Watch every token -
Task-Level Abstractions
Define higher-level tasks like chat, extract, classify, and generate, while LLM.API handles prompt patterns, tools, and model specifics under the hood.
Code to tasks, not models -
High-Throughput Batch APIs
Process thousands of requests in parallel with built-in rate control, retries, and aggregation, dramatically reducing latency and operational overhead for bulk workloads.
Scale jobs, not code
When to Use — When NOT to Use
Use it if...
- You need a low-cost general-purpose model for everyday chat and assistance.
- Your use case involves lightweight content generation like short emails, replies, or summaries.
- You need fast inference for many small requests in high-traffic consumer apps.
- Your use case involves simple classification, extraction, or tagging from short texts.
- You need a compact model for prototyping features before upgrading to larger models.
- Your use case involves educational bots answering basic questions without complex reasoning.
- You need inexpensive A/B testing across prompts or UX flows with many iterations.
Avoid if...
- You need state-of-the-art reasoning performance on complex, multi-step analytical tasks.
- Your workload requires handling very long documents or codebases within a single context.
- You need the highest possible quality for creative writing, strategy, or nuanced advice.
- Your workload requires strong, reliable tool-use orchestration across many dependent steps.
- You need advanced domain expertise for legal, medical, or highly specialized technical decisions.
- Your workload requires robust multilingual performance across low-resource or niche languages.
- You need top-tier code generation and refactoring for large, complex software projects.
Frequently Asked Questions
-
What is OpenAI GPT Mini Latest?
OpenAI GPT Mini Latest is a lightweight, cost-efficient language model by ~Openai designed for fast, general-purpose text generation via LLM.API.
-
What is the context window of OpenAI GPT Mini Latest?
OpenAI GPT Mini Latest supports up to an 8K token context window for prompts plus generated output combined.
-
What modalities does OpenAI GPT Mini Latest support?
OpenAI GPT Mini Latest supports text input and text output only; it does not handle images, audio, or video.
-
How does pricing work for OpenAI GPT Mini Latest on LLM.API?
On LLM.API, OpenAI GPT Mini Latest is billed per 1,000 tokens for input and output; check your LLM.API dashboard for exact current rates.
-
Is OpenAI GPT Mini Latest fast enough for real-time applications?
Yes, OpenAI GPT Mini Latest is optimized for low latency and is suitable for chatbots, inline assistants, and other real-time or interactive use cases.
-
How do I call OpenAI GPT Mini Latest through LLM.API?
Specify the model name "openai-gpt-mini-latest" in your LLM.API request along with your prompt and any temperature or max_tokens parameters.
-
How does OpenAI GPT Mini Latest compare to larger OpenAI models?
OpenAI GPT Mini Latest is cheaper and faster than larger OpenAI models but generally produces shorter, less nuanced responses and has weaker reasoning.
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What are the main limitations of OpenAI GPT Mini Latest?
OpenAI GPT Mini Latest may struggle with very long, complex reasoning, domain-expert tasks, and strict factual accuracy compared to larger models.
-
Can I use OpenAI GPT Mini Latest for code generation?
Yes, it can generate and edit code for many languages, but quality and debugging help are more limited than with larger, code-specialized models.
-
Does OpenAI GPT Mini Latest support system and user messages like ChatGPT?
Yes, LLM.API exposes a chat-style interface where you provide system and user messages that OpenAI GPT Mini Latest uses to shape its responses.
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