GPT-5.1: Everything You Need to Know (2026)

GPT-5.1: Everything You Need to Know in 2026

OpenAI's GPT-5.1 represents the latest iteration in the GPT model family, building on the foundation of GPT-5 with refined capabilities across reasoning, code generation, multimodal understanding, and instruction following. Whether you are evaluating it for personal use, team deployment, or API integration, this guide covers everything you need to know.

What Is GPT-5.1?

GPT-5.1 is an updated version of OpenAI's GPT-5 model, positioned as a refinement rather than a generational leap. Think of it as GPT-5 with improved reliability, better tool use, enhanced reasoning in edge cases, and expanded context handling.

Specification	GPT-5.1
Developer	OpenAI
Architecture	Transformer (details proprietary)
Context Window	256K tokens
Max Output	32K tokens
Training Data Cutoff	Late 2025
Multimodal	Text, images, audio, video input
Tool Use	Native function calling, code interpreter
Available Via	ChatGPT, API, Azure OpenAI

Key Improvements Over GPT-5

GPT-5.1 is not a complete new model, but it includes meaningful upgrades:

1. Improved Instruction Following

GPT-5.1 is significantly better at following complex, multi-step instructions without drifting or skipping requirements. In internal evaluations, it shows a measurable reduction in "instruction amnesia" on long prompts.

2. Enhanced Reasoning Consistency

While GPT-5 occasionally produced inconsistent reasoning chains, 5.1 demonstrates more stable chain-of-thought outputs, particularly in mathematical proofs and logical deductions.

3. Better Code Generation

Benchmark	GPT-5	GPT-5.1	Improvement
HumanEval	90.2%	93.1%	+2.9%
MBPP+	85.7%	89.3%	+3.6%
SWE-bench Verified	52.1%	57.8%	+5.7%
LiveCodeBench	71.3%	76.2%	+4.9%

4. Expanded Multimodal Capabilities

GPT-5.1 handles complex visual reasoning better, including multi-image comparisons, dense document parsing, and video frame analysis with improved temporal understanding.

5. Function Calling Reliability

For developers using GPT-5.1 through the API, function calling (tool use) is more reliable with fewer hallucinated parameters and better schema adherence.

How to Access GPT-5.1

ChatGPT (Web and Mobile)

Go to chat.openai.com
If you are a Plus, Team, or Enterprise subscriber, select GPT-5.1 from the model picker
Free tier users may have limited access to GPT-5.1 (check current availability)

OpenAI API

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.1",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain the CAP theorem with a practical example."}
    ],
    "temperature": 0.7,
    "max_tokens": 2048
  }'

Using the Python SDK:

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "Write a Python function that implements binary search with detailed comments."}
    ],
    temperature=0,
    max_tokens=2048
)

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

Using the Node.js SDK:

import OpenAI from 'openai';

const openai = new OpenAI();

const completion = await openai.chat.completions.create({
  model: 'gpt-5.1',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Design a REST API for a task management app.' }
  ],
  temperature: 0.7,
});

console.log(completion.choices[0].message.content);

Azure OpenAI

For enterprise users on Azure:

curl "https://YOUR_RESOURCE.openai.azure.com/openai/deployments/gpt-51/chat/completions?api-version=2025-12-01" \
  -H "Content-Type: application/json" \
  -H "api-key: $AZURE_OPENAI_API_KEY" \
  -d '{
    "messages": [
      {"role": "user", "content": "Summarize the key changes in GDPR 2025 amendments."}
    ]
  }'

GPT-5.1 Pricing

Tier	Input Tokens	Output Tokens	Notes
Standard	$2.50 / 1M tokens	$10.00 / 1M tokens	Default tier
Batch API	$1.25 / 1M tokens	$5.00 / 1M tokens	50% discount, async
Cached Input	$1.25 / 1M tokens	$10.00 / 1M tokens	For repeated prompts

Cost comparison with other models:

Model	Input (per 1M)	Output (per 1M)
GPT-5.1	$2.50	$10.00
GPT-4o	$2.50	$10.00
Claude Opus 4	$15.00	$75.00
Claude Sonnet 4	$3.00	$15.00
Gemini 2.5 Pro	$1.25	$10.00

When to Use GPT-5.1 vs. Other Models

Use Case	Best Model	Why
Complex coding tasks	GPT-5.1 or Claude Sonnet 4	Strong code gen with good instruction following
Creative writing	Claude Opus 4 or GPT-5.1	Both excel at nuanced, long-form writing
Data analysis	GPT-5.1 (with Code Interpreter)	Built-in execution environment
Quick factual answers	GPT-4o-mini or Gemini Flash	Cheaper and faster for simple queries
Math and reasoning	o3 or QwQ	Purpose-built reasoning models
Image understanding	GPT-5.1 or Gemini 2.5 Pro	Both have strong vision capabilities
Cost-sensitive apps	GPT-4o-mini or Claude Haiku	10-20x cheaper per token
Enterprise compliance	GPT-5.1 via Azure	Azure's enterprise security features

Advanced Features

Function Calling (Tool Use)

GPT-5.1 has improved function calling with better parameter extraction:

from openai import OpenAI

client = OpenAI()

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get current weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "City and state, e.g. San Francisco, CA"
                    },
                    "unit": {
                        "type": "string",
                        "enum": ["celsius", "fahrenheit"]
                    }
                },
                "required": ["location"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    tools=tools,
    tool_choice="auto"
)

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

Structured Outputs

Force GPT-5.1 to return valid JSON matching a specific schema:

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {"role": "user", "content": "List 3 programming languages with their key features"}
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "languages",
            "schema": {
                "type": "object",
                "properties": {
                    "languages": {
                        "type": "array",
                        "items": {
                            "type": "object",
                            "properties": {
                                "name": {"type": "string"},
                                "paradigm": {"type": "string"},
                                "key_feature": {"type": "string"}
                            },
                            "required": ["name", "paradigm", "key_feature"]
                        }
                    }
                },
                "required": ["languages"]
            }
        }
    }
)

Vision (Image Input)

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this image? Describe it in detail."},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/photo.jpg"
                    }
                }
            ]
        }
    ]
)

Tips for Getting the Best Results

Use system messages effectively. GPT-5.1 is very responsive to well-crafted system prompts. Define the role, tone, constraints, and output format clearly.
Set temperature based on task. Use 0 for factual/coding tasks, 0.7-1.0 for creative tasks.
Use structured outputs when you need reliable JSON. Do not just ask for JSON in the prompt; use the response_format parameter.
Leverage the 256K context window for long document analysis, but be mindful of cost. Input tokens add up fast with large contexts.
Use the Batch API for non-time-sensitive workloads. You get 50% off and results within 24 hours.
Compare with o3 for pure reasoning tasks. GPT-5.1 is a generalist; o3 is a reasoning specialist.

Wrapping Up

GPT-5.1 is a solid evolution of GPT-5, delivering meaningful improvements in reliability, code generation, and multimodal understanding without a dramatic price increase. For most developers, it is a strong default choice for general-purpose LLM tasks.

The AI landscape is broader than just language models, though. If your application also needs image generation, video creation, lip sync, voice cloning, or other media capabilities, Hypereal AI provides a unified API that lets you access GPT-5.1 alongside dozens of specialized AI models, all through a single integration.

GPT-5.1: Everything You Need to Know in 2026

What Is GPT-5.1?

Specification	GPT-5.1
Developer	OpenAI
Architecture	Transformer (details proprietary)
Context Window	256K tokens
Max Output	32K tokens
Training Data Cutoff	Late 2025
Multimodal	Text, images, audio, video input
Tool Use	Native function calling, code interpreter
Available Via	ChatGPT, API, Azure OpenAI

Key Improvements Over GPT-5

GPT-5.1 is not a complete new model, but it includes meaningful upgrades:

1. Improved Instruction Following

2. Enhanced Reasoning Consistency

While GPT-5 occasionally produced inconsistent reasoning chains, 5.1 demonstrates more stable chain-of-thought outputs, particularly in mathematical proofs and logical deductions.

3. Better Code Generation

Benchmark	GPT-5	GPT-5.1	Improvement
HumanEval	90.2%	93.1%	+2.9%
MBPP+	85.7%	89.3%	+3.6%
SWE-bench Verified	52.1%	57.8%	+5.7%
LiveCodeBench	71.3%	76.2%	+4.9%

4. Expanded Multimodal Capabilities

GPT-5.1 handles complex visual reasoning better, including multi-image comparisons, dense document parsing, and video frame analysis with improved temporal understanding.

5. Function Calling Reliability

For developers using GPT-5.1 through the API, function calling (tool use) is more reliable with fewer hallucinated parameters and better schema adherence.

How to Access GPT-5.1

ChatGPT (Web and Mobile)

Go to chat.openai.com
If you are a Plus, Team, or Enterprise subscriber, select GPT-5.1 from the model picker
Free tier users may have limited access to GPT-5.1 (check current availability)

OpenAI API

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.1",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain the CAP theorem with a practical example."}
    ],
    "temperature": 0.7,
    "max_tokens": 2048
  }'

Using the Python SDK:

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "Write a Python function that implements binary search with detailed comments."}
    ],
    temperature=0,
    max_tokens=2048
)

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

Using the Node.js SDK:

import OpenAI from 'openai';

const openai = new OpenAI();

const completion = await openai.chat.completions.create({
  model: 'gpt-5.1',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Design a REST API for a task management app.' }
  ],
  temperature: 0.7,
});

console.log(completion.choices[0].message.content);

Azure OpenAI

For enterprise users on Azure:

curl "https://YOUR_RESOURCE.openai.azure.com/openai/deployments/gpt-51/chat/completions?api-version=2025-12-01" \
  -H "Content-Type: application/json" \
  -H "api-key: $AZURE_OPENAI_API_KEY" \
  -d '{
    "messages": [
      {"role": "user", "content": "Summarize the key changes in GDPR 2025 amendments."}
    ]
  }'

GPT-5.1 Pricing

Tier	Input Tokens	Output Tokens	Notes
Standard	$2.50 / 1M tokens	$10.00 / 1M tokens	Default tier
Batch API	$1.25 / 1M tokens	$5.00 / 1M tokens	50% discount, async
Cached Input	$1.25 / 1M tokens	$10.00 / 1M tokens	For repeated prompts

Cost comparison with other models:

Model	Input (per 1M)	Output (per 1M)
GPT-5.1	$2.50	$10.00
GPT-4o	$2.50	$10.00
Claude Opus 4	$15.00	$75.00
Claude Sonnet 4	$3.00	$15.00
Gemini 2.5 Pro	$1.25	$10.00

When to Use GPT-5.1 vs. Other Models

Use Case	Best Model	Why
Complex coding tasks	GPT-5.1 or Claude Sonnet 4	Strong code gen with good instruction following
Creative writing	Claude Opus 4 or GPT-5.1	Both excel at nuanced, long-form writing
Data analysis	GPT-5.1 (with Code Interpreter)	Built-in execution environment
Quick factual answers	GPT-4o-mini or Gemini Flash	Cheaper and faster for simple queries
Math and reasoning	o3 or QwQ	Purpose-built reasoning models
Image understanding	GPT-5.1 or Gemini 2.5 Pro	Both have strong vision capabilities
Cost-sensitive apps	GPT-4o-mini or Claude Haiku	10-20x cheaper per token
Enterprise compliance	GPT-5.1 via Azure	Azure's enterprise security features

Advanced Features

Function Calling (Tool Use)

GPT-5.1 has improved function calling with better parameter extraction:

from openai import OpenAI

client = OpenAI()

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get current weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "City and state, e.g. San Francisco, CA"
                    },
                    "unit": {
                        "type": "string",
                        "enum": ["celsius", "fahrenheit"]
                    }
                },
                "required": ["location"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    tools=tools,
    tool_choice="auto"
)

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

Structured Outputs

Force GPT-5.1 to return valid JSON matching a specific schema:

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {"role": "user", "content": "List 3 programming languages with their key features"}
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "languages",
            "schema": {
                "type": "object",
                "properties": {
                    "languages": {
                        "type": "array",
                        "items": {
                            "type": "object",
                            "properties": {
                                "name": {"type": "string"},
                                "paradigm": {"type": "string"},
                                "key_feature": {"type": "string"}
                            },
                            "required": ["name", "paradigm", "key_feature"]
                        }
                    }
                },
                "required": ["languages"]
            }
        }
    }
)

Vision (Image Input)

response = client.chat.completions.create(
    model="gpt-5.1",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this image? Describe it in detail."},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/photo.jpg"
                    }
                }
            ]
        }
    ]
)

Tips for Getting the Best Results

Use system messages effectively. GPT-5.1 is very responsive to well-crafted system prompts. Define the role, tone, constraints, and output format clearly.
Set temperature based on task. Use 0 for factual/coding tasks, 0.7-1.0 for creative tasks.
Use structured outputs when you need reliable JSON. Do not just ask for JSON in the prompt; use the response_format parameter.
Leverage the 256K context window for long document analysis, but be mindful of cost. Input tokens add up fast with large contexts.
Use the Batch API for non-time-sensitive workloads. You get 50% off and results within 24 hours.
Compare with o3 for pure reasoning tasks. GPT-5.1 is a generalist; o3 is a reasoning specialist.

Hypereal로 구축 시작하기

GPT-5.1: Everything You Need to Know in 2026

What Is GPT-5.1?

Key Improvements Over GPT-5

How to Access GPT-5.1

ChatGPT (Web and Mobile)

OpenAI API

Azure OpenAI

GPT-5.1 Pricing

When to Use GPT-5.1 vs. Other Models

Advanced Features

Function Calling (Tool Use)

Structured Outputs

Vision (Image Input)

Tips for Getting the Best Results

Wrapping Up

관련 아티클

GPT-5: 알아야 할 모든 것 (2026)

2026년 최고의 오픈 소스 RAG 프레임워크

2026년 최고의 Qwen 모델들: 완벽 비교 분석

지금 바로 개발을 시작하세요

Hypereal로 구축 시작하기

GPT-5.1: Everything You Need to Know in 2026

What Is GPT-5.1?

Key Improvements Over GPT-5

How to Access GPT-5.1

ChatGPT (Web and Mobile)

OpenAI API

Azure OpenAI

GPT-5.1 Pricing

When to Use GPT-5.1 vs. Other Models

Advanced Features

Function Calling (Tool Use)

Structured Outputs

Vision (Image Input)

Tips for Getting the Best Results

Wrapping Up

관련 아티클

GPT-5: 알아야 할 모든 것 (2026)

2026년 최고의 오픈 소스 RAG 프레임워크

2026년 최고의 Qwen 모델들: 완벽 비교 분석

지금 바로 개발을 시작하세요