hf.co/mradermacher/gemma-4-E4B-GGUF:Q6_K

gemma4 · 7.52B · unknown

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 24, 2026 · Submitted by AAA

Top 93% Compare

Global Score

41 /100

Marginal

Hardware Fit

100/100

Quality

16/100

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Ollama

ollama pull hf.co/mradermacher/gemma-4-E4B-GGUF:Q6_K

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ollama.com/library/hf.co/mradermacher/gemma-4-E4B-GGUF

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GGUF versions & quantizations

Hardware

Machine: MacBook Pro
CPU: Apple M1 Pro
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 16 GB LPDDR5
GPU: Apple M1 Pro
OS: macOS 26.6.2
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 34.6
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: 179 ms
Time to first token How fast the model starts responding — lower is better: 179 ms
Load time Time to load the model into memory before inference: 3.9 s
Memory usage RAM consumed during inference — percentage of total system memory: 3.9 GB (25%)
Total tokens Total number of tokens generated across all benchmark prompts: 1304

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

5/20

Coding

7/20

Instruction following

0/20

Structured output

0/15

Math

3/15

Multilingual

1/10

Category levels

Reasoning: Poor Coding: Weak Instruction Following: Poor Structured Output: Poor Math: Poor Multilingual: Poor

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: be57f2e7bfc4a170a180896dae8d164d761046e2af57c7fd79bd5781d0465ccc

Interpretation

Hardware fit: 100/100. Overall suitability: MARGINAL (Global 41/100). Category profile: Reasoning: Poor, Coding: Weak, Instruction Following: Poor, Structured Output: Poor, Math: Poor, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 25% (peak 33%)

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Or run without installing: npx metrillm@latest