GPT-5 Mini by OpenAI — 400K Context
Faster, cost-efficient version of GPT-5 suitable for well-defined tasks and precise prompts.
At a glance
Modalities
Context window
400,000
Pricing
input / output per 1M
Reasoning
Capabilities
Streaming
Real-time token-by-token response streaming
Function calling
Connect the model to external tools and systems
Structured outputs
Return responses in JSON schema format
Web search
Search the internet for real-time information
File search
Search and retrieve from uploaded files
Code execution
Execute code in a sandboxed environment
Details
| Knowledge cutoff | 2024-05-31 |
| Model ID | gpt-5-mini |
| Provider | OpenAI |
Rate limits
| Tier | RPM | TPM | Batch queue |
|---|---|---|---|
| Tier1 | 500 | 500,000 | 5,000,000 |
| Tier2 | 5,000 | 2,000,000 | 20,000,000 |
| Tier3 | 5,000 | 4,000,000 | 40,000,000 |
| Tier4 | 10,000 | 10,000,000 | 1,000,000,000 |
| Tier5 | 30,000 | 180,000,000 | 15,000,000,000 |
What You Need to Know About GPT-5 Mini
Complete Overview of GPT-5 Mini by OpenAI
Get detailed information about GPT-5 Mini, including its context window of 400000 tokens, pricing per million tokens, supported input and output modalities, and benchmark scores. This model from OpenAI offers specific capabilities for natural language processing, code generation, and complex reasoning tasks that set it apart from alternatives.
Pricing and Cost Analysis for GPT-5 Mini
Compare input and output token pricing for GPT-5 Mini against other models in its class. Understanding LLM pricing is essential for budgeting your AI applications at scale. We break down the cost per million tokens for both input and output so you can estimate the total cost of your workloads and compare value across providers.
Benchmarks and Performance Metrics for GPT-5 Mini
Review benchmark performance data for GPT-5 Mini across key evaluation metrics. Compare its reasoning, coding, and language understanding capabilities against competing models to determine if it is the right fit for your specific requirements, whether that involves complex analysis, creative generation, or efficient inference at scale.