Activefrontierllm Proprietary

GPT-4.1

by OpenAI· Released April 2025· Cutoff June 2024

GPT-4.1 is OpenAI's latest flagship language model, offering improved performance across coding, instruction following, and long-context tasks. It features a 1M token context window, making it ideal for processing large documents and codebases. GPT-4.1 replaces GPT-4 Turbo as the most capable model in the GPT-4 series.

Official Site API Docs

Input cost

$2.00 per 1M tokens

Output cost

$8.00 per 1M tokens

Context window

1,000,000 tokens

Max output

32,768 tokens

Modalities

text

License

proprietary

Capabilities

Function CallingCode GenerationStreamingJSON ModeLong ContextInstruction FollowingStructured Outputs

Best For

Complex coding tasks, long-document analysis, and applications requiring precise instruction following with very large contexts.

Strengths

Industry-leading 1M token context window
Superior coding performance on benchmarks like SWE-bench
Improved instruction following and reduced hallucination
Cost-effective pricing compared to GPT-4 Turbo

Limitations

Not multimodal (text-only, no vision or audio)
Higher latency than smaller models like GPT-4o mini
May still exhibit biases present in training data
Not open source; usage subject to OpenAI's API policies

Use Cases

Analyzing entire codebases for refactoring or bug detection

Processing and summarizing large legal or financial documents

Building advanced coding assistants with deep context understanding

Automating complex multi-step workflows with function calling

Generating and reviewing long-form technical documentation

Powering customer support bots that reference extensive knowledge bases

Assisting in scientific research by analyzing full-length papers

Improvements Over Previous Model

Context window increased from 128K tokens (GPT-4 Turbo) to 1M tokens
Pricing reduced: $2/$8 per 1M tokens vs $10/$30 for GPT-4 Turbo
Improved coding benchmarks: SWE-bench score increased from 38% to 52%
Better instruction following and reduced hallucination rates
Max output tokens increased from 4,096 to 32,768
Lower latency and faster response times

Back to all models

Use Cases

Analyzing entire codebases for refactoring or bug detection

Processing and summarizing large legal or financial documents

Building advanced coding assistants with deep context understanding

Automating complex multi-step workflows with function calling

Generating and reviewing long-form technical documentation

Powering customer support bots that reference extensive knowledge bases

Assisting in scientific research by analyzing full-length papers

Improvements Over Previous Model

Context window increased from 128K tokens (GPT-4 Turbo) to 1M tokens

Pricing reduced: $2/$8 per 1M tokens vs $10/$30 for GPT-4 Turbo

Improved coding benchmarks: SWE-bench score increased from 38% to 52%

Better instruction following and reduced hallucination rates

Max output tokens increased from 4,096 to 32,768

Lower latency and faster response times