Hy-Memory-30B-A3B · Q8_0
This page aggregates 1 real-world runs of Hy-Memory-30B-A3B (Q8_0) on NVIDIA RTX Spark with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.
58.7 tok/s
Decode
Decode speed
210.79 tok/s
Prefill
Prefill speed
1.41 s
TTFT
Time to first token
74.55 GB
VRAM
VRAM usage
1
Measured runs
1
Independent sources
Other
Source platforms
16 days ago
Last verified
Performance
- llama.cpp · FP16 Decode 42.81 · Prefill 164.71 ·
- llama.cpp · Q5_K_M Decode 67.28 · Prefill 348.21 ·
- llama.cpp · Q8_0 (current)Decode 58.7 · Prefill 210.79 ·
- Ollama · Q5_K_M Decode 64.27 · Prefill 274.24 ·
- Ollama · Q8_0 Decode 46.83 · Prefill 233.52 ·
- llama.cpp · IQ4_XS Decode 93.67 · Prefill 407.31 ·
- llama.cpp · Q4_K_M Decode 85.75 · Prefill 321.23 ·
- Ollama · IQ4_XS Decode 76.19 · Prefill 410.3 ·
- Ollama · Q4_K_M Decode 69.54 · Prefill 373.27 ·
Core figures
- Decode (avg)
- 58.7 tok/s
- Prefill (avg)
- 210.79 tok/s
- TTFT (avg)
- 1.41 s
- VRAM (avg)
- 74.55 GB
- MTP acceptance rate
- —
- TTFB
- 0.47 GB
- Power draw
- 73.8 W
Configuration
Member-level fields are taken from the most recent run
- Model
- Hy-Memory-30B-A3B
- Quantization
- Q8_0
- Framework
- llama.cpp
- Version
- v0.55
- Context length
- 32768 tokens
- Batch size
- 256
- GPU layers
- 33
- Flash Attention
- On
Hardware
Nominal and measured figures are shown side by side; whether it runs is the reader's call
- GPU
- NVIDIA RTX Spark
- Nominal VRAM
- 128 GB
- Measured VRAM (avg)
- 74.55 GB
- OS
- Ubuntu 24.04
- Driver
- 615.78
- CUDA
- 13.0
- Power draw
- 73.8 W
- Reference price
- $2,399 · updated 2026-10-19
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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
v0.55 · Ubuntu 24.04 · CUDA 13.0 · 32768 ctx
58.7 tok/s
Decode
210.79 tok/s
Prefill
1.41 s
TTFT
74.55 GB
VRAM
—
MTP
73.8 W
Power draw
L2 batch seed 2026-10-20 (Linux 116GiB unlock): llama.cpp on Spark running model_id=87 at Q8_0