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google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · 7.9B · Q4_K_M

Excellent

Nov 1, 2026 · AMD RYZEN AI MAX+ 395

ornith-1.5:9b

OLLAMA GGUF

qwen35 · 9.0B · Q4_K_M

Good

Aug 24, 2026 · Apple M1 Pro

Global Score
80 vs 69
Hardware Fit
83 vs 95
Quality Score
79 vs 58

Hardware

google/gemma-4-e4b ornith-1.5:9b
MachineGMKtec EVO-X3MacBook Pro
CPUAMD RYZEN AI MAX+ 395Apple M1 Pro
Cores3210
RAM120 GB16 GB
GPUAMD Radeon(TM) 8060S GraphicsApple M1 Pro
OSMicrosoft Windows 11 Pro 10.0.26300macOS 26.6.2
Archx64arm64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b ornith-1.5:9b
Tokens/sec46.522.2
First chunk14 ms341 ms
TTFT1.9 s341 ms
Load time7.6 s4.8 s
Memory usage0.0 GB7.1 GB
Memory %0%45%

HW Fit Score Breakdown

google/gemma-4-e4b

Speed
43/50
TTFT
10/20
Memory
30/30

ornith-1.5:9b

Speed
49/50
TTFT
20/20
Memory
26/30

Quality

google/gemma-4-e4b

Reasoning
14/20
Coding
18/20
Instruction
15/20
Structured
15/15
Math
7/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Weak Multilingual: Strong

ornith-1.5:9b

Reasoning
19/20
Coding
15/20
Instruction
6/20
Structured
2/15
Math
15/15
Multilingual
1/10
Reasoning: Strong Coding: Adequate Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Poor
View google/gemma-4-e4b details | View ornith-1.5:9b details

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$ npm install -g metrillm@latest
$ metrillm

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Or run without installing: npx metrillm@latest