BenchLM is tracking Gemma 4 E2B by Google. Some benchmark data is visible, but not enough non-generated coverage is available for a leaderboard rank yet.
BenchLM is tracking Gemma 4 E2B, but this profile is currently excluded from the public leaderboard because it still lacks enough verified benchmark coverage to rank safely. Only verified public benchmark rows appear below.
Gemma 4 E2B is a open weight model with a 128K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
Gemma 4 E2B sits inside the Gemma 4 family alongside Gemma 4 31B, Gemma 4 26B A4B, Gemma 4 E4B. This profile currently has 6 of 125 tracked benchmarks. BenchLM only exposes verified benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Multimodal & Grounded (#91). This performance profile makes it particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Provider
GoogleSource Type
Open WeightReasoning
ReasoningContext Window
128K
Model Status
Current
Release Date
Apr 2, 2026Overall Score
Unranked
Pricing
$0.00 / $0.00
Input / output per 1M
Runtime
N/A
Latency unavailable
BenchLM is still missing enough verified benchmark coverage to rank this model across the public leaderboard. Only verified public benchmark rows are shown below.
Gemma 4 E2B has 6 verified benchmark scores on BenchLM, but it does not yet have enough coverage to receive a global overall rank.
Gemma 4 E2B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Gemma 4 E2B has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.
Gemma 4 E2B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Gemma 4 E2B ranks #91 out of 103 models in multimodal and grounded tasks benchmarks with an average score of 44.2. There are stronger options in this category.
Yes, Gemma 4 E2B is an open weight model created by Google, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Gemma 4 E2B belongs to the Gemma 4 family. Related variants on BenchLM include Gemma 4 31B, Gemma 4 26B A4B, Gemma 4 E4B.
Not yet. Gemma 4 E2B currently has 6 verified benchmark scores out of the 125 benchmarks BenchLM tracks. BenchLM only exposes verified public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
Gemma 4 E2B has a context window of 128K, which determines how much text it can process in a single interaction.
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