GPT 5.1
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GPT 5.1

gpt-5.1llms.txt
OpenAI
GPT-5 is OpenAI’s most advanced language model, designed for complex tasks that require step-by-step reasoning, precise instruction following, and high reliability. It improves reasoning, code generation, and prompt understanding—including test-time routing and intent cues like “think hard about this”—while reducing hallucination and sycophancy.

Pricing

PricingCache ReadImage GenerationWeb Search
$1.25$10
$0.125/M tokens-$0.01/request

Input Modalities

  • Text
  • Vision

Output Modalities

  • Text

Capabilities

  • Thinking
  • Web
  • DeepSearch
  • Tools
  • Tool calling
  • Structured outputs

Providers

Azure gpt-5.1
Pricing$1.25$10
Cache Read$0.125/M tokens
Web Search$0.01/request
Context400K
Max output128K
Latency2.4S
Throughput63.9TPS
Uptime
99.96% uptime 2 days ago
99.97% uptime yesterday
99.99% uptime today
OpenAI gpt-5.1
Pricing$1.25$10
Cache Read$0.125/M tokens
Web Search$0.01/request
Context400K
Max output128K
Latency2.3S
Throughput71.4TPS
Uptime
0.00% uptime 2 days ago
100.00% uptime yesterday
0.00% uptime today

Performance for gpt-5.1

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-5.1",
    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 5.1?

GPT-5 is OpenAI’s most advanced language model, designed for complex tasks that require step-by-step reasoning, precise instruction following, and high reliability. It improves reasoning, code generation, and prompt understanding—including test-time routing and intent cues like “think hard about this”—while reducing hallucination and sycophancy.