OpenAI just released GPT-4.1, a powerful new model family specifically designed for developers that outperforms GPT-4.0 across multiple benchmarks while offering significant cost savings. Available exclusively via API, this release brings major improvements in coding, instruction following, and context handling.
GPT-4.1: A New Family of Developer-Focused Models
As of April 2025, OpenAI has introduced three variants in the GPT-4.1 family:
- GPT-4.1: The flagship model
- GPT-4.1 Mini: A smaller yet surprisingly capable variant
- GPT-4.1 Nano: OpenAI’s first ultra-lightweight, high-speed model
What makes this release particularly noteworthy is the unprecedented 1 million token context window available across all three models—without the premium pricing that competitors typically charge for extended context.
Performance Improvements That Matter for Developers
The benchmarks for GPT-4.1 are impressive, particularly in areas critical to developers:
- 54.6% on SWE-verified benchmarks (21.4% improvement over GPT-4.0)
- 38.3% on instruction-following scales (10.5% increase over GPT-4.0)
- 72% on video MME for multimodal understanding (6.7% improvement)
Perhaps most striking is GPT-4.1 Mini’s performance—it matches or exceeds GPT-4.0 in intelligence evaluations while reducing latency by nearly half and costs by an impressive 83%.
The Surprising GPT-4.5 Deprecation
In an unexpected move, OpenAI announced they’re deprecating GPT-4.5 Preview, which was released just weeks ago. The model will be turned off on July 14, 2025, giving developers three months to transition.
According to Kevin Wheel, OpenAI’s Chief Product Officer, the decision comes down to GPU allocation—they need the computing resources that were powering GPT-4.5 to support the more efficient and practical GPT-4.1 family. While this transition may cause frustration for developers who recently integrated GPT-4.5, the company positions it as a necessary step stemming from their research findings.
Real-World Improvements in Code Generation
Early access partners have reported significant improvements in practical coding scenarios:
- Windsurf reports 60% higher scores than GPT-4.0 on internal coding benchmarks
- 30% more efficient tool calling and 50% fewer unnecessary edits
- Better at generating code “diffs” instead of rewriting entire files
- Substantially improved frontend coding capabilities
Kodo’s testing showed that across 200 real-world pull requests, GPT-4.1 produced better suggestions in 55% of cases while being notably less verbose than other models—a critical improvement for developer workflows.
Needle-in-a-Haystack: Making the Million-Token Context Useful
Having a million-token context is only valuable if the model can effectively use it. OpenAI demonstrated GPT-4.1’s capabilities by having it identify a single non-standard line hidden within NASA’s 450,000-token server logs from 1995—a task impossible with previous models.
This capability scored 100% on retrieval benchmarks, showing the model can not only ingest massive amounts of data but meaningfully process and analyze it.
Pricing That Makes Sense for API Use
The pricing structure for the GPT-4.1 family is designed to be developer-friendly:
- GPT-4.1: $2.00 per million tokens input, $8.00 output ($1.84 blended)
- GPT-4.1 Mini: $0.40 input, $1.60 output ($0.42 blended)
- GPT-4.1 Nano: $0.10 input, $0.40 output ($0.12 blended)
These rates represent significant cost reductions compared to previous models, making advanced AI capabilities more accessible for production applications.
Instruction Following: The Developer Experience Upgrade
One of the most frustrating aspects of working with LLMs has been their inconsistency in following specific instructions. GPT-4.1 shows a 49% accuracy rate on OpenAI’s hard instruction-following evaluation—a substantial improvement over GPT-4.0’s 29%.
This improvement means fewer prompt engineering workarounds and more reliable API responses, particularly valuable for production applications where consistency is critical.
GPT-4.1 represents a significant step forward for AI development tools—offering better performance at lower costs with the massive context window developers have been requesting. While the deprecation of GPT-4.5 may be disruptive for early adopters, the practical benefits of the 4.1 family appear to justify the transition. For developers looking to build more capable, cost-effective AI applications, GPT-4.1—particularly the standout Mini variant—deserves immediate attention.