gpt-5.4-mini β API, Pricing & Context Window | Vivgrid
gpt-5.4-mini on Vivgrid: a fast, low-cost GPT-5.4 model with a 400K context window, PDF and image input, and three-region acceleration.
gpt-5.4-mini is the cost-efficient sibling of gpt-5.4, tuned for high-throughput workloads where speed and price matter more than maximum reasoning depth. It still offers a generous 400K-token context window plus image and PDF input.
On Vivgrid it is geo-distributed across AMER, EMEA, and APAC, making it a strong default for latency-sensitive, high-volume agent traffic worldwide.
Specifications
| Provider | OpenAI |
| Model ID | gpt-5.4-mini |
| Best for | General-purpose |
| Context window | 400,000 tokens |
| Max output | 128,000 tokens |
| Modalities | Text, Image, Pdf |
| Tool / function calling | Yes |
| Knowledge cutoff | 2025-08 |
| Acceleration | β‘ Geo-Distributed β AMER, EMEA, APAC |
Pricing
Pricing in USD per 1M tokens, matching the provider's rates.
| Input | Cached input | Output |
|---|---|---|
| $0.75 | $0.08 | $4.50 |
Quick start
Call gpt-5.4-mini through Vivgrid's unified, OpenAI-compatible endpoint. Get an API key from the Vivgrid Console.
curl https://api.vivgrid.com/v1/chat/completions \
-H "Authorization: Bearer $VIVGRID_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.4-mini",
"messages": [
{ "role": "user", "content": "Say hello in English, Chinese and Spanish." }
],
"stream": true
}'Ideal use cases
- High-volume agents and chat backends with tight cost budgets
- Document understanding over PDFs and images
- Classification, extraction, and routing tasks
- Real-time experiences where latency is critical
Related models
- gpt-5.4 β the full-size, higher-quality model
- gpt-5.4-nano β the smallest, cheapest 5.4 tier
- gpt-5-mini β earlier-generation mini model
gpt-5.1-codex
gpt-5.1-codex on Vivgrid: a Codex-tuned coding model on the Responses API with a 400K context window and three-region geo-distributed acceleration.
gpt-5.4-nano
gpt-5.4-nano on Vivgrid: the smallest, most economical GPT-5.4 model with a 400K context window and image and PDF input for high-scale tasks.