Small models trade Doom accuracy for 15x faster reactions

A builder tested four small language models as real-time Doom controllers, posting the results to r/LocalLLaMA on September 20. The gap between them matters for anyone building agents that have to act under a real-time clock rather than reply at their own pace. The model with the fastest reactions scored a quarter as many kills as the model with the best aim.

The test ran ViZDoom at 320x240 on a 35 Hz clock, targeting five decisions per second. Each model got a deterministic text description of visible objects and HUD values instead of raw pixels. The builder averaged eight seeds per scenario on a DGX Spark.

Jev 1.13 won on kills, averaging 5.63 per run with a 117.3ms median response time. A finetuned Qwen3.5-4B LoRA scored 3.63 kills at 146.8ms, slower and less accurate than Jev. Laya English and a finetuned ModernCE-base-nli model tied at 1.25 kills each, answering in 16.2ms and 7.6ms.

It's a narrow test, four models, one game, one hardware setup. The results don't say whether a larger model closes the gap without adding proportional latency, or whether they hold outside ViZDoom's simplified HUD-and-object description format.