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Hy-Memory-30B-A3B · Q5_K_M

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NVIDIA H100 80GB HBM380GBvLLM v0.27L2 Cross-framework verified

This page aggregates 1 real-world runs of Hy-Memory-30B-A3B (Q5_K_M) on NVIDIA H100 80GB HBM3 with vLLM, contributed by 1 independent source platforms; metrics are averages of published measurements.

299.81 tok/s

Decode

Decode speed

1,193.35 tok/s

Prefill

Prefill speed

1.68 s

TTFT

Time to first token

60.69 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 · Q6_K Decode 289.84 · Prefill 1568.48 ·
  2. vLLM · IQ2_XS Decode 346.16 · Prefill 1601.93 ·
  3. vLLM · Q5_K_M (current)Decode 299.81 · Prefill 1193.35 ·

Core figures

Decode (avg)
299.81 tok/s
Prefill (avg)
1,193.35 tok/s
TTFT (avg)
1.68 s
VRAM (avg)
60.69 GB
MTP acceptance rate
—
TTFB
2.4 GB
Power draw
618.3 W

Configuration

Member-level fields are taken from the most recent run

Model
Hy-Memory-30B-A3B
Quantization
Q5_K_M
Framework
vLLM
Version
v0.27
Context length
16384 tokens
Batch size
8
GPU layers
999
Flash Attention
Off

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)
60.69 GB
OS
Ubuntu 22.04
Driver
565.57
CUDA
13.0
Power draw
618.3 W

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

    v0.27 · Ubuntu 22.04 · CUDA 13.0 · 16384 ctx

    299.81 tok/s

    Decode

    1,193.35 tok/s

    Prefill

    1.68 s

    TTFT

    60.69 GB

    VRAM

    —

    MTP

    618.3 W

    Power draw

    L2 batch seed 2026-10-19: vLLM on hw_id=55 running model_id=87 at Q5_K_M