llamaperf

Qwen3.8 27B Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-NEO

on 2× NVIDIA Tesla P40 24GB · llama.cpp · 220,160 ctx

Tone: positiveNVIDIA hardware
Sep 7, 2026
Throughput
46.0 t/s gen · 444.4 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
Q8_0 (GGUF)
KV cache
F16
System RAM
64 GB
VRAM reported
24 GB

Use cases

coding

Summary

User reports about 46 t/s on typical short interactive decode in use on dual P40s, up from roughly 15 t/s without speculative decoding. Setup is MTP speculative decoding with draft-mtp and ngram-simple, draft maximum 6, Qwen reasoning medium and the F16 vision projector loaded. A synthetic 128-token decode reached 48 t/s, long-context interactive decode runs at about 20 t/s, and prefill is 444 t/s at pp512. The model is a fine-tune of Qwen3.8 27B.