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Model comparison

Gemma 4 E2B vs K-Exaone

Data verified

Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

41.65/100
Margin
6.7pts
winning →
LG AI Research
48.32/100
0 category wins0 category wins

BenchAlign evidence: Gemma 4 E2B estimated; K-Exaone estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemma 4 E2B and K-Exaone share 12 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to Gemma 4 E2B; 0 to K-Exaone.

Updated July 16, 2026
Shared results
12
Gemma 4 E2B only
3
K-Exaone only
0
Comparable categories
0 / 8

Benchmark data for Gemma 4 E2B and K-Exaone is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

K-Exaone has the larger context window at 256K, compared with 128K for Gemma 4 E2B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Gemma 4 E2B and K-Exaone
CategoryGemma 4 E2BΔK-Exaone
KnowledgeGemma 4 E2B56.9MarginNo overlapK-ExaoneNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemma 4 E2BK-ExaoneComparison
Input / output priceUSD per 1M tokensGemma 4 E2B$0 input / $0 outputK-ExaoneNot availableA complete price comparison is not available.
Generation speedtokens per secondGemma 4 E2BNot availableK-ExaoneNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemma 4 E2BNot availableK-ExaoneNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemma 4 E2B128KK-Exaone256KK-Exaone lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemma 4 E2BK-ExaoneResult
τ²-bench resultsSource 20.8%74.3%K-Exaone leads
Coding
BenchmarkGemma 4 E2BK-ExaoneResult
Terminal-Bench HardSource 3.0%22.7%K-Exaone leads
AA-SciCodeSource 20.9%35.6%K-Exaone leads
Reasoning
BenchmarkGemma 4 E2BK-ExaoneResult
AA-LCRSource 15.0%55.7%K-Exaone leads
CritPtSource 0.0%1.1%K-Exaone leads
Knowledge
BenchmarkGemma 4 E2BK-ExaoneResult
GPQASource 43.4%Not comparable
MMLU-ProSource 60%Not comparable
Artificial Analysis Intelligence IndexSource 9.3%24.7%K-Exaone leads
AA-GPQA DiamondSource 43.3%78.3%K-Exaone leads
AA-HLESource 4.8%13.1%K-Exaone leads
AA-Omniscience IndexSource -24.0%-57.9%Gemma 4 E2B leads
AA-Omniscience AccuracySource 6.7%16.5%K-Exaone leads
AA-Omniscience Hallucination RateSource 32.9%89.1%Gemma 4 E2B leads
Multimodal
BenchmarkGemma 4 E2BK-ExaoneResult
AA-MMMU-ProSource 44.6%Not comparable
Inst. Following
BenchmarkGemma 4 E2BK-ExaoneResult
AA-IFBenchSource 38.0%64.7%K-Exaone leads
Frequently Asked Questions (3)

Can I compare Gemma 4 E2B and K-Exaone on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Gemma 4 E2B and K-Exaone today?

Gemma 4 E2B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 16, 2026

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