qwen2.5:72b

qwen2 · 72.7B · Q4_K_M

NVIDIA NVIDIA_DGX_Spark (Cortex-X925)

122 GB · Ubuntu 24.04.4 LTS

Tested on June 27, 2026

Top 43% Compare

Global Score

75 /100

Not Rec.

Hardware Fit

50/100

Quality

86/100

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Ollama

ollama pull qwen2.5:72b

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ollama.com/library/qwen2.5

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GGUF versions & quantizations

Hardware

Machine: NVIDIA NVIDIA_DGX_Spark
CPU: Cortex-X925
Cores: 20 total (20 perf)
Frequency: 3.35 GHz
RAM: 122 GB
GPU: Device 2e12
OS: Ubuntu 24.04.4 LTS
Arch: arm64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 4.4
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 529 ms
Time to first token How fast the model starts responding — lower is better: 529 ms
Load time Time to load the model into memory before inference: 49.7 s
Memory usage RAM consumed during inference — percentage of total system memory: 54.0 GB (44%)
Total tokens Total number of tokens generated across all benchmark prompts: 1168

Score breakdown

Speed

4/50

Time to first token

20/20

Memory

26/30

Quality

Reasoning

19/20

Coding

19/20

Instruction following

12/20

Structured output

14/15

Math

12/15

Multilingual

10/10

Category levels

Reasoning: Strong Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Strong Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.30.10
Model format: GGUF
Hardware profile: HIGH-END
Result hash: 292e6e8c51832320f5ea57a53d8520dba51ad21a619bde325fcf02c8d5737e82

Interpretation

Hardware fit: 50/100. Overall suitability: NOT RECOMMENDED (Global 75/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Disqualifiers

Token speed too low: 4.4 tok/s (minimum: 7 tok/s for HIGH-END profile)

Bench Environment

Thermal: nominal Swap delta: +0.1 GB CPU load: avg 14% (peak 30%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest