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Qwen3.8-27B · IQ4_XS

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NVIDIA RTX 309024GBllama.cpp b4200L0 Self-reported

This page aggregates 1 real-world runs of Qwen3.8-27B (IQ4_XS) on NVIDIA RTX 3090 with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

50 tok/s

Decode

Decode speed

375 tok/s

Prefill

Prefill speed

0.27 s

TTFT

Time to first token

15.1 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 (current)Decode 50 · Prefill 375 ·
  2. llama.cpp · Q5_K_S Decode 40.1 · Prefill 300.8 ·
  3. llama.cpp · IQ3_XXS Decode 76.9 · Prefill 576.8 ·
  4. llama.cpp · IQ3_S Decode 67 · Prefill 502.5 ·
  5. llama.cpp · Q6_K Decode 30.8 · Prefill 231 ·
  6. llama.cpp · Q4_K_M Decode 44.5 · Prefill 333.8 ·

Core figures

Decode (avg)
50 tok/s
Prefill (avg)
375 tok/s
TTFT (avg)
0.27 s
VRAM (avg)
15.1 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
IQ4_XS
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 3090
Nominal VRAM
24 GB
Measured VRAM (avg)
15.1 GB
OS
Linux
Driver
570.65
CUDA
12.6

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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

    50 tok/s

    Decode

    375 tok/s

    Prefill

    0.27 s

    TTFT

    15.1 GB

    VRAM

    —

    MTP

    — W

    Power draw

    L0 理论估算(add-1000-records-batch3)