google/gemma-4-e4b

gemma4 · Q4_K_M

LENOVO 82JQ (AMD Ryzen 7 5800H)

16 GB · Microsoft Windows 11 家庭版中文版 10.0.26100

Tested on July 7, 2026

Top 64% Compare

Global Score

68 /100

Good

Hardware Fit

93/100

Quality

57/100

Get this model

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

MLX versions & conversions

Hardware

Machine: LENOVO 82JQ
CPU: AMD Ryzen 7 5800H
Cores: 16 total (16 perf)
Frequency: 3.2 GHz
RAM: 16 GB DDR4
GPU: NVIDIA GeForce RTX 3060 Laptop GPU
OS: Microsoft Windows 11 家庭版中文版 10.0.26100
Arch: x64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 26.2
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.2
First chunk latency Delay before the first streamed chunk arrives from runtime: 17 ms
Time to first token How fast the model starts responding — lower is better: 572 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 6.5 GB (41%)
Total tokens Total number of tokens generated across all benchmark prompts: 1591

Score breakdown

Speed

46/50

Time to first token

20/20

Memory

27/30

Quality

Reasoning

17/20

Coding

19/20

Instruction following

4/20

Structured output

4/15

Math

12/15

Multilingual

1/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio
Model format: GGUF
Hardware profile: BALANCED
Result hash: f6aa775a96df9943814ea1a68f699d0a10b9a23bd8cf9557dc3934c35f5df9d5

Interpretation

Hardware fit: 93/100. Overall suitability: GOOD (Global 68/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Poor, Structured Output: Weak, Math: Strong, Multilingual: Poor.

Warnings

Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.

Bench Environment

Power: AC Swap delta: +0.0 GB CPU load: avg 41% (peak 49%)

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