gemma-3-4b-it-q4-k-m

llama · 4B · Q4_K_M

Mac Pro (Intel Core™ i5-10400)

32 GB · macOS 26.5.1

Tested on July 9, 2026

Top 34% Compare

Global Score

80 /100

Excellent

Hardware Fit

100/100

Quality

71/100

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Ollama

ollama pull gemma-3-4b-it-q4-k-m

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ollama.com/library/gemma-3-4b-it-q4-k-m

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GGUF versions & quantizations

Hardware

Machine: Mac Pro
CPU: Intel Core™ i5-10400
Cores: 12 total (12 perf)
Frequency: 2.9 GHz
RAM: 32 GB Empty
GPU: AMD Radeon RX 6700 XT
OS: macOS 26.5.1
Arch: x64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 75.0
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±5.9
First chunk latency Delay before the first streamed chunk arrives from runtime: 136 ms
Time to first token How fast the model starts responding — lower is better: 136 ms
Load time Time to load the model into memory before inference: 0.0 s
Memory usage RAM consumed during inference — percentage of total system memory: 0.8 GB (3%)
Total tokens Total number of tokens generated across all benchmark prompts: 2931

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

11/20

Coding

17/20

Instruction following

14/20

Structured output

14/15

Math

5/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.5.18
Model format: GGUF
Hardware profile: BALANCED
Result hash: 8142c6c616ae8864975a170d7abc96cecd81cdb754914c58c83ea3eb4929502d

Interpretation

Hardware fit: 100/100. Overall suitability: EXCELLENT (Global 80/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Bench Environment

Thermal: nominal Power: AC CPU load: avg 20% (peak 32%)

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