Google/Dense

GoogleGemma 4 E4B

Gemma 4 E4B — 4.5B effective params from 8B total. Vision + audio, 128K context. Top of its class.

chatmultilingualvisionaudio
8B
Parameters
128K
Context length
17
Benchmarks
6
Quantizations
200K
HF downloads
Architecture
Dense
Released
2026-04-02
Layers
42
KV Heads
2
Head Dim
256
Family
gemma

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.895.4 GBgood
Q5_K_S5.576.1 GBgood
Q5_K_M5.76.2 GBgood
Q6_K6.567.0 GBexcellent
Q8_08.59.0 GBlossless
FP161616.5 GBlossless

Select your GPU above to see speed estimates and compatibility for each quantization.

READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN GEMMA 4 E4B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (17)

IFEval73.8
MMLU-PRO69.4
GPQA Diamond58.6
LiveCodeBench52.0
IFBench44.2
AIME42.5
BBH33.1
AA Long Context30.7
SciCode24.4
MATH23.2
τ²-Bench20.8
AA Intelligence18.8
MUSR15.0
GPQA14.2
AA Coding13.7
Terminal-Bench8.3
HLE3.7

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run gemma4:e4b-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 3050 6GB
6 GB VRAM • 168 GB/s
NVIDIA
$169
Intel Arc A380
6 GB VRAM • 186 GB/s
INTEL
$129
NVIDIA RTX 2060 6GB
6 GB VRAM • 336 GB/s
NVIDIA
$150
NVIDIA GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
$140
NVIDIA Tesla C2070
6 GB VRAM • 143 GB/s
NVIDIA
NVIDIA Tesla C2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla C2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla M2070
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2070-Q
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2070
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla K20X
6 GB VRAM • 250 GB/s
NVIDIA
NVIDIA Tesla K20Xm
6 GB VRAM • 250 GB/s
NVIDIA

Find the best GPU for Gemma 4 E4B

Build Hardware for Gemma 4 E4B
▸ SPEC SHEET

Gemma 4 E4B8B Dense.

▸ SPECIFICATIONS
PARAMETERS
8B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, multilingual, vision, audio
RELEASE DATE
2026-04-02
PROVIDER
Google
FAMILY
gemma
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.895.4 GB94%
Q5_K_S5.576.1 GB96%
Q5_K_M5.76.2 GB96%
Q6_K6.567.0 GB97%
Q8_08.59.0 GB100%
FP161616.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO69.4
MATH23.2
IFEval73.8
BBH33.1
GPQA14.2
MUSR15.0
GPQA Diamond58.6
HLE3.7
AA Intelligence18.8
AA Coding13.7
LiveCodeBench52.0
AIME42.5
aa_ifbench44.2
aa_terminal_bench8.3
aa_tau220.8
aa_scicode24.4
aa_lcr30.7
§ 02RUN COMMAND

Run Gemma 4 E4B locally with Ollama — needs 5.4 GB VRAM at Q4_K_M:

$ollama run gemma4:e4b