用 Codex 让 Astra、Sol 和 Luna 玩《晨风》：GPT-6 三款模型同一任务表现差异明显

I’ve been working on AstraBridge, a specialized interface for OpenMW that lets LLM agents play Morrowind through a modified OpenMW build. I’m using Codex as the agent runtime, and one of the things I wanted to test was how differently the models behave when given exactly the same game environment and tools.

A small disclaimer first: this is not a pure real-time screen + mouse + keyboard setup. The agent gets screenshots of the game window, controls, and a semantic/action interface for things a normal player could perceive or do: movement, dialogue, inventory, journal, combat, UI interaction, persistent memory, etc. The game pauses after each turn so the model has time to reason.

It does not get quest stages, hidden actors, global coordinates, save internals, walkthroughs, or other hidden game state. It also can’t see through walls. For this run, I gave GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna Max the same task: Start a new game and complete Fargoth’s Hiding Place.

I only told them where the quest begins. Same game environment, same interface, same basic starting conditions.

The difference was pretty dramatic: Astra understood the task almost immediately. It found the quest NPC, figured out that it needed to observe Fargoth, climbed the lighthouse, waited until night, tracked him from above, then went down and found the hidden stash. Sol 6.1 behaved remarkably similarly and completed the quest as well.

Luna 6 Max had a much harder time. It struggled with spatial orientation even during the tutorial, but eventually managed to escape the Census Office. After that, it spent roughly 10 hours of real time wandering around Seyda Neen trying to find Arrille’s Tradehouse.

It repeatedly asked NPCs for directions, explored the village, lost track of where it had already been, and kept returning to the same locked rear door of the Tradehouse without realizing that the entrance was on the other side.

Eventually I stopped the run manually. What I found interesting is that the failure wasn’t really about understanding the quest. Luna understood the high-level objective and could use the tools correctly. The problem was much more basic: maintaining a useful spatial model of the environment and recognizing when it was repeating the same unsuccessful navigation pattern. Astra and Sol were much better at that.

Video of all three runs: https://youtu.be/ckx7BxGHeso?is=SqjOGF5jflIbSTHl

AstraBridge:

https://github.com/incident201/AstraBridgeForOpenMW

This is mostly an experiment for fun, not an attempt to claim that this is a rigorous benchmark of model capabilities. I’m planning to try more models and more open-ended scenarios next.