Flex Service Tier Launched: 50% Reduced Pricing for Select OpenAI Models

Date: 2025-12-15 / (1404-09-24)

Summary

AvalAI introduces the Flex Service Tier, offering 50% reduced pricing for select OpenAI models. This new pricing tier provides significant cost savings for batch processing, non-time-sensitive workloads, and high-volume API usage in exchange for higher latency.

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Details

What is the Flex Service Tier?

The Flex Service Tier is a new pricing option that offers 50% reduced costs compared to the default tier for select OpenAI models. This tier is designed for workloads where cost savings are more important than response latency.

Key Features

• 50% Cost Reduction: Pay half the default rate for supported models
• Opt-in Parameter: Simply add "service_tier": "flex" to your API requests
• Response Tracking: All API responses include the service_tier field indicating which tier was used
• Seamless Integration: Works with existing OpenAI-compatible SDKs

Supported Models

The Flex Service Tier is available for the following OpenAI models:

Model	Model Aliases
gpt-5.2	gpt-5.2-2025-12-11
gpt-5.1	gpt-5.1-2025-11-13
gpt-5	gpt-5-2025-08-07
gpt-5-mini	gpt-5-mini-2025-08-07
gpt-5-nano	gpt-5-nano-2025-08-07
o3	-
o4-mini	-

Flex Tier Pricing

Prices are per 1 million tokens and represent 50% savings compared to default tier pricing.

Model	Input	Cached Input	Output
gpt-5.2	$0.875	$0.0875	$7.00
gpt-5.1	$0.625	$0.0625	$5.00
gpt-5	$0.625	$0.0625	$5.00
gpt-5-mini	$0.125	$0.0125	$1.00
gpt-5-nano	$0.025	$0.0025	$0.20
o3	$1.00	$0.25	$4.00
o4-mini	$0.55	$0.138	$2.20

Important Considerations

⚠️ Latency and Reliability

The Flex tier has higher latency compared to the default tier:

• Requests may take longer to process
• Server timeout can be up to 900 seconds (15 minutes)
• Requests may time out or fail during processing
• Recommended for: Batch processing, non-time-sensitive tasks, background jobs
• Not recommended for: Interactive applications, real-time assistants, user-facing interfaces

⚠️ Credit Package Limitation

Credit packages do NOT cover Flex tier costs. When using service_tier: "flex", costs are deducted from your standard account balance, not from credit package allocations.

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API Request/Response Examples

Example Request

curl https://api.avalai.ir/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "gpt-5-mini",
    "messages": [
      {
        "role": "user",
        "content": "Summarize the key points of machine learning."
      }
    ],
    "service_tier": "flex"
  }'

Example Response

{
  "id": "chatcmpl-123",
  "created": 1765789075,
  "model": "gpt-5-mini-2025-08-07",
  "object": "chat.completion",
  "system_fingerprint": null,
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed. Key points include:\n\n1. **Supervised Learning**: Training with labeled data\n2. **Unsupervised Learning**: Finding patterns in unlabeled data\n3. **Reinforcement Learning**: Learning through trial and error\n4. **Deep Learning**: Neural networks with multiple layers\n5. **Applications**: Image recognition, NLP, recommendation systems",
        "role": "assistant",
        "annotations": []
      }
    }
  ],
  "usage": {
    "completion_tokens": 150,
    "prompt_tokens": 20,
    "total_tokens": 170,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  },
  "service_tier": "flex",
  "estimated_cost": {
    "unit": "0.0001525000",
    "irt": 20.03,
    "exchange_rate": 131350
  }
}

Unsupported Model Error

If you attempt to use the Flex tier with an unsupported model:

curl https://api.avalai.ir/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "gpt-5.4-mini",
    "messages": [{"role": "user", "content": "hi"}],
    "service_tier": "flex"
  }'

Error Response:

{
  "error": {
    "message": "Model 'gpt-5.4-mini' does not support service_tier='flex'. Flex tier is only available for: gpt-5, gpt-5-2025-08-07, gpt-5-mini, gpt-5-mini-2025-08-07, gpt-5-nano, gpt-5-nano-2025-08-07, gpt-5.1, gpt-5.1-2025-11-13, gpt-5.2, gpt-5.2-2025-12-11, o3, o4-mini. checkout https://docs.avalai.ir/fa/service-tiers for more information.",

    "type": "invalid_request",
    "param": null,
    "code": "invalid_request",
    "request_id": "019b214f-4f5d-7321-8a3a-59f89d473c7c"
  }
}

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SDK Usage Examples

Bash

curl https://api.avalai.ir/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "gpt-5-mini",
    "messages": [
      {
        "role": "user",
        "content": "Summarize the key points of machine learning."
      }
    ],
    "service_tier": "flex"
  }'

Python

from openai import OpenAI

client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")

# Use flex tier for cost savings on non-time-sensitive tasks
response = client.chat.completions.create(
    model="gpt-5-mini",
    messages=[
        {
            "role": "user",
            "content": "Summarize the key points of machine learning.",
        }
    ],
    service_tier="flex",
)

print(response.choices[0].message.content)
print(f"Service tier used: {response.service_tier}")

JavaScript

import { OpenAI } from "openai";

const client = new OpenAI({
  apiKey: process.env.AVALAI_API_KEY,
  baseURL: "https://api.avalai.ir/v1",
});

// Use flex tier for cost savings on non-time-sensitive tasks
const response = await client.chat.completions.create({
  model: "gpt-5-mini",
  messages: [
    {
      role: "user",
      content: "Summarize the key points of machine learning.",
    },
  ],
  service_tier: "flex"
});

console.log(response.choices[0].message.content);
console.log(`Service tier used: ${response.service_tier}`);

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Best Practices

When to Use Flex Tier

• Batch Processing: Processing large amounts of data where time is not critical
• Background Tasks: Scheduled jobs, data analysis, content generation
• Cost Optimization: When cost reduction is the priority and you can tolerate delays
• Non-Production Workloads: Testing, development, experimentation

When to Use Default (Standard) Tier

• Interactive Applications: Chatbots, real-time assistants, user-facing interfaces
• Time-Sensitive Tasks: When quick responses are required
• Production Workflows: Where reliability is critical
• Credit Package Usage: When you want costs covered by credit packages

Implementing Retry Logic

For production applications using Flex tier, implement retry logic with fallback to default tier:

def make_request_with_fallback(messages, model="gpt-5-mini"):
    # First, try flex tier for cost savings
    try:
        response = client.chat.completions.create(
            model=model,
            messages=messages,
            service_tier="flex",
            timeout=900,  # 15 minute timeout
        )
        return response, "flex"
    except Exception as e:
        print(f"Flex tier failed: {e}. Falling back to default...")

    # Fall back to default tier
    response = client.chat.completions.create(
        model=model, messages=messages, service_tier="default"
    )
    return response, "default"

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Related Links

• Service Tiers Documentation - Comprehensive guide to service tiers
• Pricing - Complete pricing information
• Credit Packages - Credit package limitations with Flex tier
• Chat Completions API - API reference with service_tier parameter
• Responses API - Responses API with service_tier parameter