LLM Models/Gemma 4 E4B

Gemma 4 E4B by Google DeepMind — 128K Context

4.5B effective parameter (8B with Per-Layer Embeddings) on-device model with 128K token context. Supports text, image, and audio input with text output. Designed for efficient local execution on laptops and mobile devices with native ASR and speech-to-translated-text capabilities. Features configurable thinking, function calling, and multilingual support in 140+ languages.

At a glance

Modalities

Context window

128,000

Pricing

/

input / output per 1M

Reasoning

Enabled

Capabilities

Streaming

Real-time token-by-token response streaming

Function calling

Connect the model to external tools and systems

Structured outputs

Return responses in JSON schema format

Fine-tuning

Custom model training on your data

Reasoning

Extended thinking before responding

Benchmarks

MMLU PRO 69.4
AIME 2026 42.5
LIVECODEBENCH V6 52.0
CODEFORCES ELO 940
GPQA DIAMOND 58.6
TAU2 AVG 42.2
BIGBENCH EXTRA HARD 33.1
MMMLU 76.6
MMMU PRO 52.6
OMNIDOCBENCH 1 5 0.181
MATH VISION 59.5
MEDXPERTQA MM 28.7
LONG CONTEXT MRCR V2 25.4
COVOST 35.54
FLEURS 0.08

Details

Release date 2026-05-01
Model ID gemma-4-e4b
Provider Google DeepMind

What You Need to Know About Gemma 4 E4B

Complete Overview of Gemma 4 E4B by Google DeepMind

Get detailed information about Gemma 4 E4B, including its context window of 128000 tokens, pricing per million tokens, supported input and output modalities, and benchmark scores. This model from Google DeepMind offers specific capabilities for natural language processing, code generation, and complex reasoning tasks that set it apart from alternatives.

Pricing and Cost Analysis for Gemma 4 E4B

Compare input and output token pricing for Gemma 4 E4B against other models in its class. Understanding LLM pricing is essential for budgeting your AI applications at scale. We break down the cost per million tokens for both input and output so you can estimate the total cost of your workloads and compare value across providers.

Benchmarks and Performance Metrics for Gemma 4 E4B

Review benchmark performance data for Gemma 4 E4B across key evaluation metrics. Compare its reasoning, coding, and language understanding capabilities against competing models to determine if it is the right fit for your specific requirements, whether that involves complex analysis, creative generation, or efficient inference at scale.