Back to search results

Qwen3.8-27B · Q6_K

Start a discussion
NVIDIA RTX 509032GBllama.cpp b4200L0 Self-reported

This page aggregates 1 real-world runs of Qwen3.8-27B (Q6_K) on NVIDIA RTX 5090 with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

59 tok/s

Decode

Decode speed

442.5 tok/s

Prefill

Prefill speed

0.23 s

TTFT

Time to first token

24.2 GB

VRAM

VRAM usage

L0 Self-reported

1

Measured runs

1

Independent sources

Other

Source platforms

Today

Last verified

Performance

  1. llama.cpp · IQ4_XS Decode 95.7 · Prefill 717.8 ·
  2. llama.cpp · Q5_K_S Decode 76.8 · Prefill 576 ·
  3. llama.cpp · IQ3_XXS Decode 147.1 · Prefill 1103.3 ·
  4. llama.cpp · IQ3_S Decode 128.2 · Prefill 961.5 ·
  5. llama.cpp · Q6_K (current)Decode 59 · Prefill 442.5 ·
  6. vLLM · Q4_K_M Decode 92.9 · Prefill 696.8 ·

Core figures

Decode (avg)
59 tok/s
Prefill (avg)
442.5 tok/s
TTFT (avg)
0.23 s
VRAM (avg)
24.2 GB
MTP acceptance rate
—
TTFB
— GB
Power draw
— W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3.8-27B
Quantization
Q6_K
Framework
llama.cpp
Version
b4200
Context length
4096 tokens
Batch size
512
GPU layers
99
Flash Attention
On

Hardware

Nominal and measured figures are shown side by side; whether it runs is the reader's call

GPU
NVIDIA RTX 5090
Nominal VRAM
32 GB
Measured VRAM (avg)
24.2 GB
OS
Linux
Driver
570.65
CUDA
12.6

Get started

Original model resources

Base model resources may not match this quantization. Use the verified deployment weights above when available.

Sources & evidence

1 measured records in total, each traceable to its original source

  1. L0 Self-reportedOtherOriginal link Verified on 2026-10-06

    b4200 · Linux · CUDA 12.6 · 4096 ctx

    59 tok/s

    Decode

    442.5 tok/s

    Prefill

    0.23 s

    TTFT

    24.2 GB

    VRAM

    —

    MTP

    — W

    Power draw

    L0 理论估算(add-1000-records-batch3)