When was Gemma 4 E2B released?

Gemma 4 E2B was released on April 2, 2026 by Google. This is the official Gemma 4 E2B release date tracked on LLM Stats.

Is Gemma 4 E2B available via API?

Yes, Gemma 4 E2B is available via API. See the official documentation for authentication and endpoint details.

How big is Gemma 4 E2B?

Gemma 4 E2B has 5.1 billion parameters. It ships as an open-weight model, so you can download and run it on your own hardware.

Who created Gemma 4 E2B?

Gemma 4 E2B was created by Google.

What is the license for Gemma 4 E2B?

Gemma 4 E2B is released under the Apache 2.0 license. This is an open-source / open-weight license that permits self-hosting.

What is the knowledge cutoff date for Gemma 4 E2B?

Gemma 4 E2B has a knowledge cutoff of January 2025, meaning it was trained on data up to that point and may not know about events after it.

Is Gemma 4 E2B multimodal?

Yes, Gemma 4 E2B is multimodal and can accept both text and images as input.

Where is the Gemma 4 E2B paper or technical report?

Gemma 4 E2B has a paper or technical report available at https://huggingface.co/blog/gemma4. Use that source for architecture, training, release and evaluation details.

What models should I compare Gemma 4 E2B against?

Common Gemma 4 E2B comparisons include Gemma 4 E2B vs Qwen2-VL-72B-Instruct, Gemma 4 E2B vs Claude 3 Sonnet, Gemma 4 E2B vs Qwen3-235B-A22B-Instruct-2507. Compare them side by side for benchmark scores, pricing, context window, latency and API availability.

Gemma 4 E2B API Pricing, Context Window & Benchmarks

Name: Gemma 4 E2B
Author: Google

Gemma 4 E2B: API Pricing, Context Window & Benchmarks

Gemma 4 E2B is a language model from Google, released in April 2026, with multimodal input.

Gemma 4 E2B is Google DeepMind's smallest multimodal model with 2.3 billion effective parameters (5.1B with embeddings) and a 128K context window. Supports image, text, and audio inputs. Designed for on-device and edge deployment with

Gemma 4 E2B benchmarks

Capability tiers

Standing within each category, adjusted for leaderboard depth.

Real tasks performance

High-confidence performance for Gemma 4 E2B across real-world prompt categories. Only 95% intervals at most 4 points wide are shown.

Performance by conversation depth

How Gemma 4 E2B holds up as conversations get longer.

Quality Tracker

Gemma 4 E2B Performance Across Datasets

Scores sourced from the model's scorecard, paper, or official blog posts

llm-stats.com - Sun Sep 06 2026

Notice missing or incorrect data?

Gemma 4 E2B model size

Gemma 4 E2B has 5.1 billion parameters. See how it compares to other models in the same parameter range.

Parameters

5.1B

Small (3–10B)

5.1B

1B7B70B405B

Gemma 4 E2B API

Available from the model provider

Gemma 4 E2B has an official provider API. It is not currently routed through the LLM Stats gateway.

Read the official API documentation

Gemma 4 E2B latency

Gemma 4 E2B time to first token, sustained output throughput, and failed-request rate from live API traffic over the trailing 7 days.

Gemma 4 E2B examples

Recent arena outputs from Gemma 4 E2B, picked from the highest-ranked matchups.

Gemma 4 E2B license

Gemma 4 E2B is released under the Apache 2.0 license, which permits commercial use, has 5.1B parameters, has a knowledge cutoff of January 2025.

License: Apache 2.0; Commercial use allowed
Parameters: 5.1B
Knowledge cutoff: January 2025

Apache License 2.0 - allows commercial use

Gemma 4 E2B resources

Official sources for Gemma 4 E2B: api documentation, official launch post, model weights.

Gemma 4 E2B vs other models

The most-compared alternatives to Gemma 4 E2B are Qwen2-VL-72B-Instruct, Claude 3 Sonnet, Qwen3-235B-A22B-Instruct-2507. Open any pair side-by-side for benchmarks, pricing, context, and latency.