GPT-4.1

GPT-4.1 represents OpenAI's latest advancement in large language models, released on April 14, 2025. This model brings significant improvements in coding capabilities, instruction following, and long-context understanding compared to previous versions. The GPT-4.1 family includes three variants: GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano, each designed for different use cases and performance requirements.

The model shows major gains in coding tasks and outperforms GPT-4o across all benchmarks. With support for up to 1 million tokens of context and updated knowledge cutoff to June 2024, GPT-4.1 positions itself as a strong competitor in the current AI landscape. This comparison will analyze GPT-4.1 against same-provider models (GPT-4o, GPT-4o mini) and cross-provider competitors (Claude 4, Gemini 2.5 Pro, Grok 3).

The methodology includes technical specifications comparison, performance benchmarks analysis, pricing evaluation, and API integration examples. All comparisons use publicly available data and focus on practical use cases for developers and enterprises.

GPT-4.1 Specifications

OpenAI's GPT-4.1 comes with enhanced features that make it suitable for complex coding and long-context tasks.

GPT-4.1 vs GPT-4o

These models represent OpenAI's current flagship offerings with different optimization focuses.

Technical Specifications Comparison

This table compares core technical specifications between GPT-4.1 and GPT-4o models.

Performance Benchmarks between GPT-4.1 vs GPT-4o

The following benchmarks show GPT-4.1's improvements in coding and reasoning tasks compared to GPT-4o.

Pricing of GPT-4.1 and GPT-4o

Pricing structures show different cost optimization strategies for each model variant.

API Integration Examples of GPT-4.1 vs GPT-4o

The API format remains consistent between models with model name being the primary difference.

# GPT-4.1 Example
import openai

client = openai.OpenAI(api_key="your-api-key")

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[
        {"role": "user", "content": "Write a Python function to sort a list"}
    ],
    max_tokens=1000
)

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

# GPT-4o Example
import openai

client = openai.OpenAI(api_key="your-api-key")

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Write a Python function to sort a list"}
    ],
    max_tokens=1000
)

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

GPT-4.1 vs GPT-4.1 mini

Both models share the same architecture but with different performance and cost profiles.

Technical Specifications Comparison

This table shows specifications differences between full GPT-4.1 and its mini variant.

Performance Benchmarks between GPT-4.1 vs GPT-4.1 mini

Performance comparison shows trade-offs between capability and efficiency.

Pricing of GPT-4.1 and GPT-4.1 mini

Mini variant offers significant cost savings with reduced capability.

GPT-4.1 vs GPT-4.1 nano

The nano variant represents OpenAI's first attempt at an ultra-efficient model.

Technical Specifications Comparison

Nano variant maintains same context capabilities with optimized performance.

Performance Benchmarks between GPT-4.1 vs GPT-4.1 nano

Nano shows further performance reduction for maximum cost efficiency.

GPT-4.1 vs Claude 4 Sonnet

This comparison examines GPT-4.1 against Anthropic's latest flagship model for understanding competitive positioning.

Claude 4 Sonnet represents Anthropic's current state-of-the-art model with strong performance in reasoning and coding tasks. The model has shown superior performance in many benchmark evaluations and is widely used for complex reasoning tasks. Both models target enterprise and developer use cases but with different strengths and optimization approaches.

Technical Specifications GPT-4.1 vs Claude 4 Sonnet

Specifications comparison shows different architectural approaches and capabilities.

Performance Benchmarks GPT-4.1 vs Claude 4 Sonnet

Benchmark comparison shows different strengths between models with Claude excelling in reasoning tasks.

Pricing comparison of GPT-4.1 vs Claude 4 Sonnet

Different pricing models reflect different provider strategies and market positioning.

API Integration Examples

Different API formats show varying integration approaches and authentication methods.

# GPT-4.1 API Example
import openai

client = openai.OpenAI(api_key="your-openai-key")

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[
        {"role": "user", "content": "Explain quantum computing"}
    ],
    max_tokens=2000
)

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

# Claude 4 Sonnet API Example
import anthropic

client = anthropic.Anthropic(api_key="your-anthropic-key")

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=2000,
    messages=[
        {"role": "user", "content": "Explain quantum computing"}
    ]
)

print(response.content[0].text)

GPT-4.1 vs Gemini 2.5 Pro

Google's Gemini 2.5 Pro offers multimodal capabilities and competitive performance across various tasks.

Technical Specifications GPT-4.1 vs Gemini 2.5 Pro

Both models offer large context windows with different architectural optimizations.

Performance Benchmarks GPT-4.1 vs Gemini 2.5 Pro

Performance shows competitive results with different model strengths in specific areas.

Pricing comparison of GPT-4.1 vs Gemini 2.5 Pro

Pricing structures show Google's competitive positioning in the market.

GPT-4.1 vs Grok 3

X's Grok 3 represents a new competitor in the AI space with real-time capabilities.

Technical Specifications GPT-4.1 vs Grok 3

Grok 3 offers unique real-time information access but with different technical capabilities.

Performance Benchmarks GPT-4.1 vs Grok 3

Limited benchmark data available for Grok 3 due to recent release.

Performance Summary

The summary table shows GPT-4.1's strong performance in coding tasks while competitors excel in specific areas.

Use Case of GPT-4.1

GPT-4.1 works best for applications requiring strong coding capabilities and long-context understanding. The model excels in software development tasks, code review, and complex problem-solving scenarios. For enterprises needing reliable coding assistance and long document analysis, GPT-4.1 provides excellent value.

However, alternatives might be better for specific use cases. Claude 4 Sonnet offers superior reasoning for analytical tasks and costs less. Gemini 2.5 Pro provides better multimodal capabilities for visual tasks. Grok 3 excels when real-time information access is critical.

Pricing Analysis for GPT-4.1