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Model comparison

Gemma 4 E2B vs Qwen3.6-27B

Data verified

Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

41.82/100
Margin
12.0pts
winning →
53.82/100
1 category wins0 category wins

Public leaderboard positions: Gemma 4 E2B #162 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemma 4 E2B and Qwen3.6-27B share 14 comparable benchmark results. 1 of 8 categories are comparable. 0 results are unique to Gemma 4 E2B; 40 to Qwen3.6-27B.

Updated July 21, 2026
Shared results
14
Gemma 4 E2B only
0
Qwen3.6-27B only
40
Comparable categories
1 / 8

Pick Qwen3.6-27B if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.6-27B is clearly ahead on the BenchAlign aggregate, 53.82 to 41.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.6-27B gives you the larger context window at 262K, 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 Qwen3.6-27B
CategoryGemma 4 E2BΔQwen3.6-27B
KnowledgeGemma 4 E2B56.9Margin← 3.6Qwen3.6-27B53.3
AgenticGemma 4 E2BNot measuredMarginNo overlapQwen3.6-27B59.3
CodingGemma 4 E2BNot measuredMarginNo overlapQwen3.6-27B77.5
MathGemma 4 E2BNot measuredMarginNo overlapQwen3.6-27B89.2
MultimodalGemma 4 E2BNot measuredMarginNo overlapQwen3.6-27B76.7

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Gemma 4 E2BB · Qwen3.6-27B

  1. GPQA

    Knowledge
    Source ↗
    A 43.4%B 87.8%
    Winner: Qwen3.6-27BΔ 44.4
    GPQA: Gemma 4 E2B scored 43.4%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark.

  2. MMLU-Pro

    Knowledge
    Source ↗
    A 60%B 86.2%
    Winner: Qwen3.6-27BΔ 26.2
    MMLU-Pro: Gemma 4 E2B scored 60%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark.

Operational comparison

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

MetricGemma 4 E2BQwen3.6-27BComparison
Input / output priceUSD per 1M tokensGemma 4 E2B$0 input / $0 outputQwen3.6-27B$0 input / $0 outputListed prices are equal.
Generation speedtokens per secondGemma 4 E2BNot availableQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemma 4 E2BNot availableQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemma 4 E2B128KQwen3.6-27B262KQwen3.6-27B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemma 4 E2BQwen3.6-27BResult
τ²-bench resultsSource 20.8%94.2%Qwen3.6-27B leads
Terminal-Bench 2.0Source —59.3%Not comparable
Claw-EvalSource —72.4%Not comparable
QwenClawBenchSource —53.4%Not comparable
QwenWebBenchSource —1487Not comparable
AndroidWorldSource —70.3%Not comparable
AA Agentic IndexSource —27.0%Not comparable
GDPval-AASource —32.0%Not comparable
GDPval-AASource —1140Not comparable
Gert LabsSource —54.84%Not comparable
Coding
BenchmarkGemma 4 E2BQwen3.6-27BResult
AA-SciCodeSource 20.9%39.8%Qwen3.6-27B leads
SWE-bench VerifiedSource —77.2%Not comparable
SWE MultilingualSource —71.3%Not comparable
SWE-bench ProSource —53.5%Not comparable
Terminal-Bench 2.0Source —59.3%Not comparable
LiveCodeBenchSource —83.9%Not comparable
NL2RepoSource —36.2%Not comparable
AA Coding IndexSource —53.7%Not comparable
Reasoning
BenchmarkGemma 4 E2BQwen3.6-27BResult
AA-LCRSource 15.0%68.7%Qwen3.6-27B leads
CritPtSource 0.0%1.1%Qwen3.6-27B leads
KnowledgeGemma 4 E2B wins
BenchmarkGemma 4 E2BQwen3.6-27BResult
GPQASource 43.4%87.8%Qwen3.6-27B leads
MMLU-ProSource 60%86.2%Qwen3.6-27B leads
Artificial Analysis Intelligence IndexSource 9.3%37.0%Qwen3.6-27B leads
AA-GPQA DiamondSource 37.5%84.2%Qwen3.6-27B leads
AA-HLESource 4.8%21.6%Qwen3.6-27B leads
AA-Omniscience IndexSource -24.0%-19.8%Qwen3.6-27B leads
AA-Omniscience AccuracySource 6.7%19.2%Qwen3.6-27B leads
AA-Omniscience Hallucination RateSource 32.9%48.3%Gemma 4 E2B leads
MMLU-ReduxSource —93.5%Not comparable
SuperGPQASource —66%Not comparable
C-EvalSource —91.4%Not comparable
HLESource —24%Not comparable
Math
BenchmarkGemma 4 E2BQwen3.6-27BResult
HMMT Feb 2025Source —93.8%Not comparable
HMMT Nov 2025Source —90.7%Not comparable
HMMT Feb 2026Source —84.3%Not comparable
MMAnswerBenchSource —80.8%Not comparable
AIME26Source —94.1%Not comparable
Multimodal
BenchmarkGemma 4 E2BQwen3.6-27BResult
AA-MMMU-ProSource 44.6%74.6%Qwen3.6-27B leads
MMMUSource —82.9%Not comparable
MMMU-ProSource —75.8%Not comparable
RealWorldQASource —84.1%Not comparable
DynaMathSource —85.6%Not comparable
MStarSource —81.4%Not comparable
SimpleVQASource —56.1%Not comparable
CharXivSource —78.4%Not comparable
CC-OCRSource —81.2%Not comparable
CountBenchSource —97.8%Not comparable
RefCOCO (avg)Source —92.5%Not comparable
ERQASource —62.5%Not comparable
Video-MME (with subtitle)Source —87.7%Not comparable
VideoMMMUSource —84.4%Not comparable
MLVU (M-Avg)Source —86.6%Not comparable
V*Source —94.7%Not comparable
Inst. Following
BenchmarkGemma 4 E2BQwen3.6-27BResult
AA-IFBenchSource 35.1%67.6%Qwen3.6-27B leads
Frequently Asked Questions (2)

Which is better, Gemma 4 E2B or Qwen3.6-27B?

Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 41.82. The biggest single separator in this matchup is GPQA, where the scores are 43.4% and 87.8%.

Which is better for knowledge tasks, Gemma 4 E2B or Qwen3.6-27B?

Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 56.9 versus 53.3. Inside this category, AA-GPQA Diamond is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Gemma 4 E2B
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even—
Model the full break-even

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