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gemma-4-e2b-it-qat

LM-STUDIO GGUF

gemma4 · Q4_K_XL

Excellent

Jun 29, 2026 · Intel Gen Intel® Core™ i9-11900H

qwen3.5:0.8b

OLLAMA GGUF

qwen35 · 873.44M · Q8_0

Good

Mar 5, 2026 · Apple M1 Max

Global Score
81 vs 62
Hardware Fit
90 vs 100
Quality Score
77 vs 46

Hardware

gemma-4-e2b-it-qat qwen3.5:0.8b
MachineDocker ContainerMacBook Pro
CPUIntel Gen Intel® Core™ i9-11900HApple M1 Max
Cores1610
RAM15 GB32 GB
GPUTigerLake-H GT1 [UHD Graphics]Apple M1 Max
OSUbuntu 26.04 LTSmacOS 26.3
Archx64arm64
Power Modeperformancebalanced

Performance

gemma-4-e2b-it-qat qwen3.5:0.8b
Tokens/sec22.265.8
First chunk67 ms230 ms
TTFT1.1 s230 ms
Load time5.4 s1.5 s
Memory usage0.0 GB2.6 GB
Memory %0%8%

HW Fit Score Breakdown

gemma-4-e2b-it-qat

Speed
40/50
TTFT
20/20
Memory
30/30

qwen3.5:0.8b

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

Quality

gemma-4-e2b-it-qat

Reasoning
10/20
Coding
17/20
Instruction
17/20
Structured
15/15
Math
8/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong

qwen3.5:0.8b

Reasoning
9/20
Coding
4/20
Instruction
11/20
Structured
13/15
Math
3/15
Multilingual
6/10
Reasoning: Weak Coding: Poor Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Adequate
View gemma-4-e2b-it-qat details | View qwen3.5:0.8b 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