Developer compares INT4 AWQ vs INT8 for Qwen3.8 27B under heavy agent load

On 2026-10-31 at 11:19, a developer posted on the Reddit r/LocalLLaMA forum sharing roughly two weeks of production logs comparing Qwen3.8 27B running in INT8 versus INT4 AWQ under heavy agent load. According to the post, the switch happened in mid-October: the earlier INT8 deployment ran on 4x RTX 3090, while the AWQ INT4 deployment runs on just 2x RTX 3090. Both setups share the same stack, vLLM with FP8 KV and DFlash2, plus the Hermes harness with its loop detector, and identical sampling parameters (temperature 1.0, top_p 0.95, top_k 20, presence_penalty 0, thinking medium). The comparison covers the int4-awq and int8 model versions, using about two weeks of logs from each.

The reported figures are: model calls dropped from 17.7k to 11.4k; loops per 1k calls rose from 1.9 to 4.7; and conversations with at least one loop rose from 6% to 12%. One inconsistency to flag: the post title writes the quantization method as "AWK" while the body text writes "AWQ INT4". As of now this is a single source, and no other report in the provided material confirms or contradicts these numbers.