EBEasy BenchmarksLLM model index
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GPT-5.5 (xhigh)
GPT-5.5 (high)
Claude Opus 4.7 (Adaptive Reasoning, Max Effort)
Gemini 3.1 Pro Preview
GPT-5.4 (xhigh)
Artificial Analysis data
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Google

Gemma 3n E4B Instruct

Gemma 3n E4B Instruct is a Google Gemma open-model profile, aimed at developers who want deployable Google-developed models rather than hosted Gemini-only access. The benchmark data is especially useful for comparing its efficiency and capability against similarly sized open and open-weight alternatives.

Introducing Gemma

Operational Metrics

Output Speed15.3 tok/s
First Token0.34s
Blended Price$0.025/M

Model Metadata

Queryable facts extracted from the upstream model payload.

ReleaseJun 26, 2025
Context Windown/a
Modalitiesn/a
API fields: release_date

Strength: Output $

Rank #1 across 325 models.

$0.040/M

Strength: Blended $

Rank #3 across 325 models.

$0.025/M

Strength: Input $

Rank #3 across 325 models.

$0.020/M

Watch Area: Speed

Rank #292 across 293 models.

15.3 tok/s

Watch Area: Overall

Rank #488 across 500 models.

6.4

Watch Area: GPQA

Rank #444 across 478 models.

29.6%

Strength Profile

Percentile score by analysis domain.

* Cost is inverted: lower input, output, and blended prices rank higher.

Benchmark Percentiles

Higher bars mean stronger relative placement.

All Benchmarks

MetricDomainValueRank
Artificial Analysis Intelligence Indexoverall6.4#488
Artificial Analysis Coding Indexcoding4.2#371
Artificial Analysis Math Indexmath14.3#220
MMLU-Proreasoning48.8%#297
GPQA
reasoning
29.6%
#444
Humanity's Last Examreasoning4.4%#359
LiveCodeBenchcoding14.6%#292
SciCodecoding, reasoning8.1%#431
MATH-500math77.1%#119
AIMEmath13.7%#115
Output Speedspeed15.3 tok/s#292
Time to First Tokenspeed0.34s#10
Blended Pricecost$0.025/M#3
Input Pricecost$0.020/M#3
Output Pricecost$0.040/M#1
Value Indexcost, overall256.0#12