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google/gemma-4-e4b

LM-STUDIO GGUF

vlm · 7.9B · Q4_K_M

Marginal

Oct 1, 2026 · AMD Ryzen 7 4800H

hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 22, 2026 · Apple M1 Pro

Global Score
59 vs 66
Hardware Fit
62 vs 100
Quality Score
58 vs 52

Hardware

google/gemma-4-e4b hf.co/empero-ai/Qw…
MachineASUSTeK COMPUTER INC. ROG Strix G513IM_G513IMMacBook Pro
CPUAMD Ryzen 7 4800HApple M1 Pro
Cores1610
RAM15 GB16 GB
GPUAMD Radeon(TM) Graphics, NVIDIA GeForce RTX 3060 Laptop GPUApple M1 Pro
OSMicrosoft Windows 11 Pro 10.0.26200macOS 26.6.2
Archx64arm64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b hf.co/empero-ai/Qw…
Tokens/sec7.140.2
First chunk41 ms325 ms
TTFT1.2 s325 ms
Load time71.7 s3.1 s
Memory usage0.9 GB4.7 GB
Memory %6%30%

HW Fit Score Breakdown

google/gemma-4-e4b

Speed
12/50
TTFT
20/20
Memory
30/30

hf.co/empero-ai/Qwen3.8…

Speed
50/50
TTFT
20/20
Memory
30/30

Quality

google/gemma-4-e4b

Reasoning
6/20
Coding
14/20
Instruction
12/20
Structured
15/15
Math
3/15
Multilingual
8/10
Reasoning: Weak Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Strong

hf.co/empero-ai/Qwen3.8…

Reasoning
15/20
Coding
9/20
Instruction
8/20
Structured
1/15
Math
15/15
Multilingual
4/10
Reasoning: Adequate Coding: Weak Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

Run yours and compare

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest