Great summary of o3-mini! Cost-efficiency and speed are impressive. How's it dealing with large context management and integration with other models? Keen to see some benchmarks!
@langchain I would like to see how we can add a coding sandbox to this tool. let's say I ask the research assistant to look up new documentation from langgraph. I would like to see the ai model also be able to code and execute a few examples and save the logs. Maybe this runs in a docker container sandbox for safety. But I would find this feature of simple benchmarking soooooo useful.
To build applications with ai agents.. Token cost is really high when llm do tool calling and communicate to get atleast a initial answer which even may not be correct. Reducing tokens prices is a need of hour rather than introducing new model every next day. Current models are sufficient enough to integrate in the workflows.
![Seungmin "그렇게, 천천히, 우리(As we are)" | [Stray Kids : SKZ-PLAYER]](http://i.ytimg.com/vi/kAzmhLHePqU/mqdefault.jpg)
Thank you legend!
thanks lance!
nice summary, thanks for sharing
Well Done
Great summary of o3-mini! Cost-efficiency and speed are impressive. How's it dealing with large context management and integration with other models? Keen to see some benchmarks!
amazing
@langchain I would like to see how we can add a coding sandbox to this tool. let's say I ask the research assistant to look up new documentation from langgraph. I would like to see the ai model also be able to code and execute a few examples and save the logs. Maybe this runs in a docker container sandbox for safety. But I would find this feature of simple benchmarking soooooo useful.
To build applications with ai agents.. Token cost is really high when llm do tool calling and communicate to get atleast a initial answer which even may not be correct. Reducing tokens prices is a need of hour rather than introducing new model every next day.
Current models are sufficient enough to integrate in the workflows.
What’s the gUI tool? Langgraph?
Langgraph Studio