GPT 5.4 Nano
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GPT 5.4 Nano

gpt-5.4-nanollms.txt
OpenAI
GPT-5.4 nano is designed for tasks where speed and cost are most important, such as classification, data extraction, ranking, and sub-agent scenarios.

Pricing

PricingCache ReadImage GenerationWeb Search
$0.2$1.25
$0.02/M tokens-$0.01/request

Input Modalities

  • Text
  • Vision

Output Modalities

  • Text

Context length

  • 400K tokens

Max output

  • 128K tokens

Capabilities

  • Thinking
  • Streaming
  • Tool calling
  • Web search
  • URL context
  • Code interpreter
  • Computer use
  • File search
  • Memory tool
  • Structured outputs
  • Citations
  • Prompt caching
  • Background mode
  • Server-side sessions

Providers

Azure gpt-5.4-nano
Pricing$0.2$1.25
Cache Read$0.02/M tokens
Web Search$0.01/request
Context400K
Max output128K
Latency2.4S
Throughput50.6TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
OpenAI gpt-5.4-nano
Pricing$0.2$1.25
Cache Read$0.02/M tokens
Web Search$0.01/request
Context400K
Max output128K
Latency0.7S
Throughput101.5TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today

Performance for gpt-5.4-nano

Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

Uptime
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Latency
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Throughput
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Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://aihubmix.com/v1",
)

response = client.chat.completions.create(
    model="gpt-5.4-nano",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

print(response.choices[0].message.content)

Frequently asked questions

What is GPT 5.4 Nano?

GPT-5.4 nano is designed for tasks where speed and cost are most important, such as classification, data extraction, ranking, and sub-agent scenarios.