Can you recommend an advanced inference model for multi-step planning in an internal productivity app?

Yes — for advanced multi-step planning in an internal productivity app, I’d recommend a reasoning-focused model rather than a general chat-first model.

Best fit

OpenAI o1 / o1-mini (if available in your stack)

• Strong at multi-step reasoning
• Better for planning, prioritization, dependency handling, and structured decision-making
• Useful when the app needs to:
  • break a goal into sub-tasks
  • weigh tradeoffs
  • follow constraints
  • produce a reliable execution plan

If you need a slightly lighter/faster option:

GPT-4.1 / GPT-4o

• Better for interactive assistant behavior
• Strong at tool use, summarization, and workflow orchestration
• Good if planning is mixed with lots of natural-language interaction and UI responsiveness matters

Recommendation by use case

• Deep multi-step planning / complex reasoning: o1
• Balanced planning + fast UX + tool calling: GPT-4.1 or GPT-4o
• Cost-sensitive production with decent reasoning: o1-mini or a smaller GPT-4-class model

Practical suggestion for an internal productivity app

A strong pattern is:

1. Use a reasoning model to generate the plan
2. Use a faster general model to:
   • rewrite it for the user
   • summarize
   • create action items
   • drive follow-up turns

This gives you better reliability for planning without making the whole app slow.

If you want one default choice

If your main requirement is advanced inference for multi-step planning, I’d start with o1.

If you tell me:

• expected latency target
• budget constraints
• whether you need tool/function calling
• whether this is for scheduling, task decomposition, or project planning

…I can recommend a more specific model and architecture.