New Models Added: GPT-5.4 Series and Gemini 3.1 Flash-Lite Preview
Date: 2026-03-10 / (1404-12-19)
Summary
We announce the addition of OpenAI's GPT-5.4 series models (GPT-5.4 Pro, GPT-5.4, and GPT-5.3 Chat) and Google's Gemini 3.1 Flash-Lite Preview. These models bring frontier reasoning capabilities, extended context windows up to 1.05M tokens, and cost-efficient multimodal processing for high-volume tasks.
Details
OpenAI
GPT-5.4 Pro
gpt-5.4-pro is OpenAI's most advanced reasoning model, designed for complex professional work. This model uses more compute to think harder and provide consistently better answers.
| Feature | Details |
|---|---|
| Context window | 1,050,000 input tokens, 128,000 output tokens |
| Training data | Up to August 31, 2025 |
| Input pricing | $30.00 / 1M tokens |
| Cached input pricing | $0.30 / 1M tokens |
| Output pricing | $180.00 / 1M tokens |
| Input modalities | Text, Image |
| Output modalities | Text |
| Supported endpoints | v1/chat/completions, v1/responses |
| Reasoning effort | medium, high, xhigh |
| Availability | Tier 2+ users |
Key Features:
- Extended Context: 1.05M token context window for handling massive codebases and documents
- Reasoning Token Support: Supports medium, high, and xhigh reasoning effort settings
- Multi-Turn Interactions: Designed for multi-turn model interactions before responding to API requests
- Web Search Support: Supports web search tool for real-time information
- Computer Use: Supports computer use capabilities
- MCP Support: Supports Model Context Protocol
Note: For prompts with >272K input tokens, pricing is 2x input and 1.5x output for the full session. GPT-5.4 Pro is designed to tackle tough problems - some requests may take several minutes to finish. Use background mode to avoid timeouts.
GPT-5.4
gpt-5.4 is OpenAI's frontier model for complex professional work, offering best intelligence at scale for agentic, coding, and professional workflows.
| Feature | Details |
|---|---|
| Context window | 1,050,000 input tokens, 128,000 output tokens |
| Training data | Up to August 31, 2025 |
| Input pricing | $2.50 / 1M tokens |
| Cached input pricing | $0.25 / 1M tokens |
| Output pricing | $15.00 / 1M tokens |
| Input modalities | Text, Image |
| Output modalities | Text |
| Supported endpoints | v1/chat/completions, v1/responses |
| Reasoning effort | none (default), low, medium, high, xhigh |
Key Features:
- Extended Context: 1.05M token context window
- Highest Reasoning: Configurable reasoning effort levels
- Full Tool Support: Web search, file search, image generation, code interpreter, hosted shell, computer use, MCP, and more
- Distillation Support: Can be used for model distillation
- Structured Outputs: Full support for structured outputs and function calling
Note: For prompts with >272K input tokens, pricing is 2x input and 1.5x output for the full session.
GPT-5.3 Chat
gpt-5.3-chat is the GPT-5.3 Instant model currently used in ChatGPT, optimized for chat use cases with high intelligence at a competitive price point.
| Feature | Details |
|---|---|
| Context window | 128,000 input tokens, 16,384 output tokens |
| Training data | Up to August 31, 2025 |
| Input pricing | $1.75 / 1M tokens |
| Cached input pricing | $0.175 / 1M tokens |
| Output pricing | $14.00 / 1M tokens |
| Input modalities | Text, Image |
| Output modalities | Text |
| Supported endpoints | v1/chat/completions, v1/responses |
Key Features:
- High Intelligence: Latest improvements for chat use cases
- Vision Support: Can process images as input
- Function Calling: Full support for function calling and structured outputs
- Streaming: Full streaming support
Note: We recommend GPT-5.2 for general API usage, but GPT-5.3 Chat is ideal for testing the latest ChatGPT improvements for conversational applications.
Google (Gemini)
Gemini 3.1 Flash-Lite Preview
gemini-3.1-flash-lite-preview is Google's most cost-efficient multimodal model, offering the fastest performance for high-frequency, lightweight tasks.
| Feature | Details |
|---|---|
| Context window | 1,048,576 input tokens, 65,536 output tokens |
| Knowledge cutoff | January 2025 |
| Input pricing | $0.25 / 1M tokens |
| Cached input pricing | $0.025 / 1M tokens |
| Output pricing | $1.50 / 1M tokens |
| Audio input pricing | $0.50 / 1M tokens |
| Audio cached input | $0.05 / 1M tokens |
| Audio output pricing | $1.50 / 1M tokens |
| Supported inputs | Text, Image, Video, Audio, PDF |
| Supported outputs | Text |
| Supported endpoints | v1/chat/completions, v1beta/ |
Key Features:
- Cost-Efficient: Most affordable Gemini model for high-volume tasks
- Fast Performance: Optimized for extremely low-latency applications
- Multimodal Input: Supports text, image, video, audio, and PDF inputs
- Thinking Support: Configurable thinking levels for step-by-step reasoning
- Structured Outputs: Full support for JSON schema and structured outputs
- Function Calling: Native function calling support
- Search Grounding: Google Search integration for accurate responses
- URL Context: Can fetch and process web content
Best Use Cases:
- Translation: Fast, cheap, high-volume translation at scale
- Transcription: Audio and video transcription without separate pipelines
- Data Extraction: Entity extraction, classification, and lightweight data processing
- Document Summarization: Parse PDFs and return concise summaries
- Model Routing: Use as a classifier to route queries to appropriate models based on task complexity
Pricing Summary
| Model | Input ($/1M tokens) | Cached Input ($/1M tokens) | Output ($/1M tokens) |
|---|---|---|---|
gpt-5.4-pro | $30.00 | $0.30 | $180.00 |
gpt-5.4 | $2.50 | $0.25 | $15.00 |
gpt-5.3-chat | $1.75 | $0.175 | $14.00 |
gemini-3.1-flash-lite-preview | $0.25 | $0.025 | $1.50 |
API Request/Response Examples
GPT-5.4 Pro Example
bash
curl https://api.avalai.ir/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gpt-5.4-pro",
"input": "Design a comprehensive distributed system architecture with fault tolerance, scalability, and security considerations for a global financial platform.",
"reasoning": {"effort": "high"}
}'GPT-5.4 Example
bash
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gpt-5.4",
"messages": [
{
"role": "user",
"content": "Implement a real-time collaborative document editor with conflict resolution."
}
],
"max_tokens": 4096
}'GPT-5.3 Chat Example
bash
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gpt-5.3-chat",
"messages": [
{
"role": "user",
"content": "Explain quantum computing in simple terms."
}
]
}'Gemini 3.1 Flash-Lite Preview Example
bash
curl https://api.avalai.ir/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $AVALAI_API_KEY" \
-d '{
"model": "gemini-3.1-flash-lite-preview",
"messages": [
{
"role": "user",
"content": "Translate the following text to German: Hey, are you down to grab some pizza later? I am starving!"
}
]
}'Response:
json
{
"id": "chatcmpl-xyz123",
"created": 1741608788,
"model": "gemini-3.1-flash-lite-preview",
"object": "chat.completion",
"system_fingerprint": null,
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "Hey, hast du Lust, später Pizza zu holen? Ich bin am Verhungern!",
"role": "assistant",
"thinking_blocks": [],
"annotations": []
}
}
],
"usage": {
"completion_tokens": 22,
"prompt_tokens": 28,
"total_tokens": 50,
"completion_tokens_details": null,
"prompt_tokens_details": {
"audio_tokens": null,
"cached_tokens": null,
"text_tokens": 28,
"image_tokens": null
}
},
"estimated_cost": {
"unit": "0.0000400000",
"irt": 4.58,
"exchange_rate": 114600
}
}SDK Usage Examples
Using GPT-5.4 Pro with Python
python
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
# Using Responses API for advanced reasoning
response = client.responses.create(
model="gpt-5.4-pro",
input="Design a comprehensive distributed system architecture for a global financial platform.",
reasoning={"effort": "high"},
)
print(response.output)Using GPT-5.4 with Python
python
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
response = client.chat.completions.create(
model="gpt-5.4",
messages=[
{"role": "system", "content": "You are an expert software architect."},
{
"role": "user",
"content": "Implement a real-time collaborative document editor with conflict resolution.",
},
],
max_tokens=4096,
)
print(response.choices[0].message.content)Using Gemini 3.1 Flash-Lite with Python
python
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
response = client.chat.completions.create(
model="gemini-3.1-flash-lite-preview",
messages=[
{
"role": "user",
"content": "Summarize the key points of this document in bullet points.",
}
],
)
print(response.choices[0].message.content)Using Gemini 3.1 Flash-Lite with Thinking
python
from openai import OpenAI
client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")
response = client.chat.completions.create(
model="gemini-3.1-flash-lite-preview",
messages=[{"role": "user", "content": "How does AI work?"}],
extra_body={"generationConfig": {"thinkingConfig": {"thinkingLevel": "high"}}},
)
print(response.choices[0].message.content)