phi4:14b

phi3 · 14.7B · Q4_K_M

NVIDIA NVIDIA_DGX_Spark (Cortex-X925)

122 GB · Ubuntu 24.04.4 LTS

Tested on June 26, 2026

Top 34% Compare

Global Score

77 /100

Good

Hardware Fit

74/100

Quality

78/100

Get this model

🦙

Ollama

ollama pull phi4:14b

View on Ollama Library

ollama.com/library/phi4

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

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: 22.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 198 ms
Time to first token How fast the model starts responding — lower is better: 198 ms
Load time Time to load the model into memory before inference: 10.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 14.7 GB (12%)
Total tokens Total number of tokens generated across all benchmark prompts: 1135

Score breakdown

Speed

24/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

18/20

Coding

18/20

Instruction following

12/20

Structured output

13/15

Math

7/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.30.10
Model format: GGUF
Hardware profile: HIGH-END
Result hash: c594c40763da3ab92977dac7e6b8c8f95250c68af0e77071916cb41d545a6974

Interpretation

Hardware fit: 74/100. Overall suitability: GOOD (Global 77/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 15% (peak 35%)

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