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google/gemma-4-e4b-it-qat

LM-STUDIO GGUF

gemma4 · Q4_0

Good

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

glm-4.7-flash:bf16

OLLAMA GGUF

deepseek2 · 29.9B · F16

Good

Jun 26, 2026 · Cortex-X925

Global Score
78 vs 76
Hardware Fit
68 vs 73
Quality Score
82 vs 77

Hardware

google/gemma-4-e4b… glm-4.7-flash:bf16
MachineDocker ContainerNVIDIA NVIDIA_DGX_Spark
CPUIntel Gen Intel® Core™ i9-11900HCortex-X925
Cores1620
RAM15 GB122 GB
GPUTigerLake-H GT1 [UHD Graphics]Device 2e12
OSUbuntu 26.04 LTSUbuntu 24.04.4 LTS
Archx64arm64
Power Modeperformanceperformance

Performance

google/gemma-4-e4b… glm-4.7-flash:bf16
Tokens/sec11.425.8
First chunk26 ms605 ms
TTFT2.2 s605 ms
Load time5.9 s44.2 s
Memory usage0.0 GB57.0 GB
Memory %0%47%

HW Fit Score Breakdown

google/gemma-4-e4b-it-qat

Speed
21/50
TTFT
17/20
Memory
30/30

glm-4.7-flash:bf16

Speed
27/50
TTFT
20/20
Memory
26/30

Quality

google/gemma-4-e4b-it-qat

Reasoning
14/20
Coding
18/20
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

glm-4.7-flash:bf16

Reasoning
13/20
Coding
17/20
Instruction
12/20
Structured
15/15
Math
10/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong

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