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Qwen3-8B · Q5_K_M

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NVIDIA RTX 509032GBOllama v0.26L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3-8B (Q5_K_M) on NVIDIA RTX 5090 with Ollama, contributed by 1 independent source platforms; metrics are averages of published measurements.

172.9 tok/s

Decode

Decode speed

940.17 tok/s

Prefill

Prefill speed

1.94 s

TTFT

Time to first token

17.72 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

Today

Last verified

Performance

  1. llama.cpp · IQ4_XS Decode 253.29 · Prefill 909.82 ·
  2. llama.cpp · Q6_K Decode 179.01 · Prefill 827.24 ·
  3. vLLM · IQ3_S Decode 284.83 · Prefill 1483.72 ·
  4. vLLM · IQ4_XS Decode 252.51 · Prefill 829.1 ·
  5. Ollama · Q5_K_M (current)Decode 172.9 · Prefill 940.17 ·
  6. llama.cpp · Q8_0 Decode 162.5 · Prefill 1218.8 ·
  7. llama.cpp · Q5_K_M Decode 236.9 · Prefill 1776.8 ·
  8. llama.cpp · Q4_K_M Decode 285.3 · Prefill 2139.8 ·

Core figures

Decode (avg)
172.9 tok/s
Prefill (avg)
940.17 tok/s
TTFT (avg)
1.94 s
VRAM (avg)
17.72 GB
MTP acceptance rate
—
TTFB
1.38 GB
Power draw
552.6 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3-8B
Quantization
Q5_K_M
Framework
Ollama
Version
v0.26
Context length
16384 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 5090
Nominal VRAM
32 GB
Measured VRAM (avg)
17.72 GB
OS
macOS 15.0
Driver
565.57
CUDA
12.8
Power draw
552.6 W

Sources & evidence

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

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

    v0.26 · macOS 15.0 · CUDA 12.8 · 16384 ctx

    172.9 tok/s

    Decode

    940.17 tok/s

    Prefill

    1.94 s

    TTFT

    17.72 GB

    VRAM

    —

    MTP

    552.6 W

    Power draw

    L2 batch seed 2026-10-10: Ollama on hw_id=13 running model_id=53 at Q5_K_M