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Qwen3.5-0.8B · Q4_K_S

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NVIDIA H100 80GB HBM380GBllama.cpp v0.30L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3.5-0.8B (Q4_K_S) on NVIDIA H100 80GB HBM3 with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

340.19 tok/s

Decode

Decode speed

1,569.8 tok/s

Prefill

Prefill speed

0.63 s

TTFT

Time to first token

3.41 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

17 days ago

Last verified

Performance

  1. llama.cpp · Q4_K_S (current)Decode 340.19 · Prefill 1569.8 ·
  2. vLLM · IQ2_M Decode 294.68 · Prefill 1324.31 ·
  3. vLLM · Q3_K_S Decode 355.68 · Prefill 1952.96 ·

Core figures

Decode (avg)
340.19 tok/s
Prefill (avg)
1,569.8 tok/s
TTFT (avg)
0.63 s
VRAM (avg)
3.41 GB
MTP acceptance rate
—
TTFB
2.72 GB
Power draw
580.3 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3.5-0.8B
Quantization
Q4_K_S
Framework
llama.cpp
Version
v0.30
Context length
32768 tokens
Batch size
512
GPU layers
20
Flash Attention
On

Hardware

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

GPU
NVIDIA H100 80GB HBM3
Nominal VRAM
80 GB
Measured VRAM (avg)
3.41 GB
OS
Ubuntu 24.04
Driver
570.86
CUDA
12.8
Power draw
580.3 W

Sources & evidence

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

  1. L2 Cross-framework verifiedOtherOriginal link Verified on 2026-10-19

    v0.30 · Ubuntu 24.04 · CUDA 12.8 · 32768 ctx

    340.19 tok/s

    Decode

    1,569.8 tok/s

    Prefill

    0.63 s

    TTFT

    3.41 GB

    VRAM

    —

    MTP

    580.3 W

    Power draw

    L2 batch seed 2026-10-19: llama.cpp on hw_id=55 running model_id=51 at Q4_K_S