We’ll keep this brief because we’re on a tight turnaround: GPT 4.1, previously known as the Quasar and Optimus models, is now live as the natural update for 4o/4o-mini (and the research preview of GPT 4.5). Though it is a general purpose model family, the headline features are:

Coding abilities (o1-level SWEBench and SWELancer, but ok Aider)

Instruction Following (with a very notable prompting guide)

Long Context up to 1m tokens (with new MRCR and Graphwalk benchmarks)

Vision (simply o1 level)

Cheaper Pricing (cheaper than 4o, greatly improved prompt caching savings)

We caught up with returning guest Michelle Pokrass and Josh McGrath to get more detail on each!

Chapters

• 00:00:00 Introduction and Guest Welcome
• 00:00:57 GPC 4.1 Launch Overview
• 00:01:54 Developer Feedback and Model Names
• 00:02:53 Model Naming and Starry Themes
• 00:03:49 Confusion Over GPC 4.1 vs 4.5
• 00:04:47 Distillation and Model Improvements
• 00:05:45 Omnimodel Architecture and Future Plans
• 00:06:43 Core Capabilities of GPC 4.1
• 00:07:40 Training Techniques and Long Context
• 00:08:37 Challenges in Long Context Reasoning
• 00:09:34 Context Utilization in Models
• 00:10:31 Graph Walks and Model Evaluation
• 00:11:31 Real Life Applications of Graph Tasks
• 00:12:30 Multi-Hop Reasoning Benchmarks
• 00:13:30 Agentic Workflows and Backtracking
• 00:14:28 Graph Traversals for Agent Planning
• 00:15:24 Context Usage in API and Memory Systems
• 00:16:21 Model Performance in Long Context Tasks
• 00:17:17 Instruction Following and Real World Data
• 00:18:12 Challenges in Grading Instructions
• 00:19:09 Instruction Following Techniques
• 00:20:09 Prompting Techniques and Model Responses
• 00:21:05 Agentic Workflows and Model Persistence
• 00:22:01 Balancing Persistence and User Control
• 00:22:56 Evaluations on Model Edits and Persistence
• 00:23:55 XML vs JSON in Prompting
• 00:24:50 Instruction Placement in Context
• 00:25:49 Optimizing for Prompt Caching
• 00:26:49 Chain of Thought and Reasoning Models
• 00:27:46 Choosing the Right Model for Your Task
• 00:28:46 Coding Capabilities of GPC 4.1
• 00:29:41 Model Performance in Coding Tasks
• 00:30:39 Understanding Coding Model Differences
• 00:31:36 Using Smaller Models for Coding
• 00:32:33 Future of Coding in OpenAI
• 00:33:28 Internal Use and Success Stories
• 00:34:26 Vision and Multi-Modal Capabilities
• 00:35:25 Screen vs Embodied Vision
• 00:36:22 Vision Benchmarks and Model Improvements
• 00:37:19 Model Deprecation and GPU Usage
• 00:38:13 Fine-Tuning and Preference Steering
• 00:39:12 Upcoming Reasoning Models
• 00:40:10 Creative Writing and Model Humor
• 00:41:07 Feedback and Developer Community
• 00:42:03 Pricing and Blended Model Costs
• 00:44:02 Conclusion and Wrap-Up