GLM-5.2 is live. #1 throughput on OpenRouter, pay-per-token on FriendliAI. Try it today ➜
Avesed
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
Avesed
Model Tree
Jackrong/Qwopus3.6-27B-v2
Input Modalities
Output Modalities
Supported Functionality
int4 weight bandwidth (fast decode) + int8 tensor-core compute (fast prefill) — the best serving quant on the NVIDIA Ampere line (A100 / RTX 3090).
vLLM gates its W4A8 kernels to Hopper. On Ampere the Marlin kernel can run W4A8-int8 but needs a small enablement patch — use vllm-ampere-optimized (prebuilt wheel + Docker image, or the standalone hot-patch). On Hopper it runs out of the box.
Same dense Qwen3.6-27B architecture as its base, so the serving profile matches the measured numbers for Avesed/Qwen3.6-27B-W4A8: ~47 tok/s single-user (sub-second TTFT), ~416 tok/s saturated on 2× RTX 3090 (tp2), ~22.8 GiB/card peak.