OpenAI Launches GPT-4.1 Model Family Focused on Real-World Coding Performance

• Model Family Launched:

  OpenAI released GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano via API. All three models outperform GPT-4o and GPT-4.5 on coding, instruction following, and long-context reasoning benchmarks. GPT-4.1 is now OpenAI’s new flagship AI model, with GPT-4.5 scheduled for deprecation on July 14, 2025.

• Context Window Upgrade:

  The models support up to 1 million tokens, a significant jump from GPT-4o’s 128K limit. This allows comprehensive ingestion of full codebases, legal corpora, or lengthy conversations. OpenAI trained GPT-4.1 to effectively ignore distractors and retrieve relevant information at any context depth.

• Real-World Engineering Goals:

  OpenAI continues to pursue the vision of an “agentic software engineer” capable of executing full software cycles—frontend/backend dev, bug resolution, QA, and documentation. This vision remains central to the model’s design.

• Coding Improvements:

  • GPT-4.1 scored 54.6% on SWE-bench Verified, a 21.4% absolute improvement over GPT-4o and 26.6% over GPT-4.5.
  • Aider’s polyglot diff benchmark showed over 2× improvement compared to GPT-4o, with extraneous edits reduced from 9% to 2%.
  • Human graders preferred GPT-4.1’s frontend app output over GPT-4o’s 80% of the time.
  • Qodo found GPT-4.1 delivered better code reviews in 55% of PRs, while Windsurf noted a 60% improvement in first-pass acceptance rates.

• Instruction Following Enhancements:

  • GPT-4.1 scored 38.3% on Scale’s MultiChallenge and 87.4% on IFEval, significantly ahead of GPT-4o.
  • Excelled in handling content constraints, response formats (e.g., YAML/Markdown), negative instructions, ranking, and multi-turn conversations.
  • Blue J reported 53% greater accuracy in legal/tax use cases. Hex saw near 2× improvement in SQL-based reasoning and schema comprehension.

• Long-Context Reliability:

  • GPT-4.1 leads in OpenAI-MRCR (multi-reference coreference) and Graphwalks (multi-hop reasoning) benchmarks.
  • Carlyle reported 50% better data extraction from long, dense financial documents.
  • Thomson Reuters saw a 17% improvement in multi-document legal analysis using GPT-4.1 in CoCounsel.

• Needle-in-Haystack & Multi-Hop Reasoning:

  Successfully retrieves specific content buried across massive context windows, a critical feature for use cases like document comparison, cross-referencing clauses, or summarizing meeting transcripts.

• Vision & Multimodal Understanding:

  GPT-4.1 mini outperformed GPT-4o on image and visual reasoning benchmarks including MMMU, MathVista, and CharXiv.

  In Video-MME (no subtitles), GPT-4.1 achieved 72%, setting a new SOTA for long-form video QA.

• Latency and Cost Efficiency:

  • GPT-4.1 is 26% cheaper than GPT-4o for typical queries.
  • Prompt caching discounts increased to 75%, up from 50%.
  • GPT-4.1 nano delivers sub-5 second first-token latency (128K input) and is ideal for tasks like autocomplete or classification.

• Pricing Table (per 1M tokens):

  Model	Input	Cached Input	Output	Blended Price
  GPT-4.1	$2.00	$0.50	$8.00	$1.84
  GPT-4.1 mini	$0.40	$0.10	$1.60	$0.42
  GPT-4.1 nano	$0.10	$0.025	$0.40	$0.12

• Developer Tools Expansion:

  OpenAI released the Codex CLI for local terminal use and enhanced API primitives like the Responses API to support low-latency, high-accuracy agentic use cases.

• Release Schedule Updates:

  • GPT-4.5 preview to be deprecated on July 14, 2025.
  • GPT-4 will be removed from ChatGPT on April 30, 2025, as GPT-4o becomes the default.
  • GPT-5 has been delayed beyond its previously expected May 2025 window, with Sam Altman citing integration complexity.
  • OpenAI is preparing to launch the o3 reasoning model and o4 mini as part of its next wave of releases.

Why This Matters:

GPT-4.1 positions OpenAI at the forefront of developer-first AI. With massive improvements across coding, instruction, and context handling, it offers enterprise-grade reliability while cutting costs and latency. Its ability to power agentic systems, long-form reasoning, and multimodal tasks sets a new bar for what AI can accomplish across software, legal, financial, and customer support domains.