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Llama-3-8B-Instruct · Q5_K_M
NVIDIA RTX 508016GBvLLM v0.37L2 Cross-framework verified
This page aggregates 1 real-world runs of Llama-3-8B-Instruct (Q5_K_M) on NVIDIA RTX 5080 with vLLM, contributed by 1 independent source platforms; metrics are averages of published measurements.
163.66 tok/s
Decode
Decode speed
702.95 tok/s
Prefill
Prefill speed
1.57 s
TTFT
Time to first token
15.2 GB
VRAM
VRAM usage
L2 Cross-framework verified
1
Measured runs
1
Independent sources
Other
Source platforms
Today
Last verified
Performance
- vLLM · Q5_K_M (current)Decode 163.66 · Prefill 702.95 ·
- Ollama · Q3_K_S Decode 209.77 · Prefill 751.17 ·
Core figures
- Decode (avg)
- 163.66 tok/s
- Prefill (avg)
- 702.95 tok/s
- TTFT (avg)
- 1.57 s
- VRAM (avg)
- 15.2 GB
- MTP acceptance rate
- —
- TTFB
- 1.31 GB
- Power draw
- 244.5 W
Configuration
Member-level fields are taken from the most recent run
- Model
- Llama-3-8B-Instruct
- Quantization
- Q5_K_M
- Framework
- vLLM
- Version
- v0.37
- Context length
- 4096 tokens
- Batch size
- 16
- GPU layers
- 999
- Flash Attention
- On
Hardware
Nominal and measured figures are shown side by side; whether it runs is the reader's call
- GPU
- NVIDIA RTX 5080
- Nominal VRAM
- 16 GB
- Measured VRAM (avg)
- 15.2 GB
- OS
- Ubuntu 24.04
- Driver
- 570.86
- CUDA
- 13.0
- Power draw
- 244.5 W
Sources & evidence
1 measured records in total, each traceable to its original source
v0.37 · Ubuntu 24.04 · CUDA 13.0 · 4096 ctx
163.66 tok/s
Decode
702.95 tok/s
Prefill
1.57 s
TTFT
15.2 GB
VRAM
—
MTP
244.5 W
Power draw
L2 batch seed 2026-10-18: vLLM on hw_id=14 running model_id=69 at Q5_K_M