GPT-4.1 family debuts: Faster, smarter, cheaper

OpenAI has launched three new AI models that outperform their predecessors across all major benchmarks while dramatically cutting costs. The GPT-4.1 family - featuring GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano - marks significant advances in coding ability, instruction following, and processing capacity.

The flagship model scores 54.6% on real-world coding tests - a 21-point jump over its predecessor. It reads and processes eight times more text than before, letting developers analyze entire codebases at once.

Speed sets these models apart. The smallest version, GPT-4.1 nano, returns results in under five seconds. The full model takes about 15 seconds for standard tasks. All three handle up to a million tokens of text - enough to process eight complete React codebases at once.

Numbers Tell the Story

Early testing shows concrete gains. Thomson Reuters saw 17% better accuracy reviewing legal documents. Windsurf reports 60% higher scores on coding tests. Blue J found 53% more accurate tax analysis.

Money Talks

Prices drop sharply across the board. The main model costs 26% less than before. The mini version matches previous performance while cutting costs by 83%. The nano model sets a new baseline for affordable AI.

Response times plummet. The nano version answers in under five seconds. The full model takes about 15 seconds with standard inputs - quick enough for real conversation.

The models excel at more than programming. They spot patterns in financial data, untangle complex legal documents, and build better websites. Human testers preferred GPT-4.1's web designs 80% of the time.

Built for Real Work

These aren't just lab improvements. Early users report concrete gains: faster development cycles, better code reviews, and sharper legal analysis. The models handle tough tasks like finding specific data in dense documents.

Cost reductions make these capabilities widely accessible. The nano model sets new standards for affordable AI. The mini version matches old performance at a fraction of the cost.

These gains stem from focused training. OpenAI built these models by working with developers to solve real problems, focusing on practical tasks like following exact instructions and writing clean code.

Technical Leap

The models break new ground in video and image understanding. GPT-4.1 scores 72% on analyzing long videos without subtitles. It spots details in charts and diagrams with 75% accuracy. The mini version often beats the old full-size model on visual tasks.

Smart Money Moves

Companies save in surprising ways. The new caching system cuts costs by 75% when processing repeated text. Batch processing adds another 50% discount. Long documents cost no extra per token - a first for the industry.

OpenAI designed these models for practical use. They follow instructions better, make fewer mistakes, and work faster than before. Early tests show they catch subtle details in documents that previous models missed.

Why this matters:

• Sharp cost drops and speed gains make advanced AI practical for daily work - from code reviews to legal analysis
• The million-token capacity lets AI tackle complex tasks that were impossible before, like analyzing entire codebases or document collections at once

Read on, my dear:

OpenAI: Introducing GPT-4.1 in the API