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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

qwen3.8-27b-mlx

LM-STUDIO MLX

qwen3_5 · 27B · 4bit

Good

Oct 20, 2026 · Apple M1 Pro

Global Score
80 vs 78
Hardware Fit
83 vs 56
Quality Score
79 vs 87

Hardware

google/gemma-4-e4b qwen3.8-27b-mlx
MachineGMKtec EVO-X3MacBook Pro
CPUAMD RYZEN AI MAX+ 395Apple M1 Pro
Cores3210
RAM120 GB32 GB
GPUAMD Radeon(TM) 8060S GraphicsApple M1 Pro
OSMicrosoft Windows 11 Pro 10.0.26300macOS 15.6.1
Archx64arm64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b qwen3.8-27b-mlx
Tokens/sec46.510.8
First chunk14 ms8 ms
TTFT1.9 s2.6 s
Load time7.6 sN/A
Memory usage0.0 GB21.0 GB
Memory %0%66%

HW Fit Score Breakdown

google/gemma-4-e4b

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

qwen3.8-27b-mlx

Speed
23/50
TTFT
16/20
Memory
17/30

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

qwen3.8-27b-mlx

Reasoning
18/20
Coding
18/20
Instruction
15/20
Structured
15/15
Math
11/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong
View google/gemma-4-e4b details | View qwen3.8-27b-mlx details

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