gemma4:26b

gemma4 · 25.8B · Q4_K_M

Mac mini (Apple M4)

24 GB · macOS 26.3

Tested on April 3, 2026 · Submitted by cryptoepops

Top 9% Compare

Global Score

85 /100

Excellent

Hardware Fit

77/100

Quality

89/100

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Ollama

ollama pull gemma4:26b

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ollama.com/library/gemma4

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GGUF versions & quantizations

Hardware

Machine: Mac mini
CPU: Apple M4
Cores: 10 total (4 perf + 6 eff)
Frequency: 2.4 GHz
RAM: 24 GB LPDDR5
GPU: Apple M4
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 24.5
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.6
First chunk latency Delay before the first streamed chunk arrives from runtime: 1.5 s
Time to first token How fast the model starts responding — lower is better: 1.5 s
Load time Time to load the model into memory before inference: 24.7 s
Memory usage RAM consumed during inference — percentage of total system memory: 20.3 GB (85%)
Total tokens Total number of tokens generated across all benchmark prompts: 1096

Score breakdown

Speed

49/50

Time to first token

20/20

Memory

8/30

Quality

Reasoning

17/20

Coding

19/20

Instruction following

17/20

Structured output

14/15

Math

12/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.20.0
Model format: GGUF
Hardware profile: ENTRY
Result hash: dd095994260a4ac19994528744e07945576df8a068ea5a951da15cca3b43f118

Interpretation

Hardware fit: 77/100. Overall suitability: EXCELLENT (Global 85/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Warnings

Significant swap activity during benchmark (+1.6 GB). Model may exceed available RAM — results are severely degraded.

Bench Environment

Power: AC Swap delta: +1.6 GB CPU load: avg 44% (peak 47%)

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