Model comparison

Gemma 4 E2B vs MAI-Thinking-1

Data verified July 23, 2026

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

Gemma 4 E2B

Google

41.82/100

No comparison

MAI-Thinking-1

Microsoft

N/A

0 category wins1 category wins

Public leaderboard positions: Gemma 4 E2B #162 (Estimated); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemma 4 E2B and MAI-Thinking-1 share 2 comparable benchmark results. 1 of 8 categories are comparable. 12 results are unique to Gemma 4 E2B; 11 to MAI-Thinking-1.

Updated July 23, 2026

Shared results: 2
Gemma 4 E2B only: 12
MAI-Thinking-1 only: 11
Comparable categories: 1 / 8

Treat this as a split decision. Gemma 4 E2B makes more sense if its workflow fits your team better; MAI-Thinking-1 is the better fit if knowledge is the priority or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Gemma 4 E2B and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

MAI-Thinking-1 gives you 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 MAI-Thinking-1
Category	Gemma 4 E2B	Δ	MAI-Thinking-1
Knowledge	Gemma 4 E2B56.9	Margin→ 15.6	MAI-Thinking-172.5
Agentic	Gemma 4 E2BNot measured	MarginNo overlap	MAI-Thinking-146.0
Coding	Gemma 4 E2BNot measured	MarginNo overlap	MAI-Thinking-165.5
Math	Gemma 4 E2BNot measured	MarginNo overlap	MAI-Thinking-189.7
Inst. Following	Gemma 4 E2BNot measured	MarginNo overlap	MAI-Thinking-185.0

Decisive benchmark drivers

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

A · Gemma 4 E2BB · MAI-Thinking-1

GPQA
Knowledge
Source ↗
A 43.4%B 84.2%
Winner: MAI-Thinking-1Δ 40.8
GPQA: Gemma 4 E2B scored 43.4%; MAI-Thinking-1 scored 84.2%. MAI-Thinking-1 wins this benchmark.
MMLU-Pro
Knowledge
Source ↗
A 60%B 85%
Winner: MAI-Thinking-1Δ 25
MMLU-Pro: Gemma 4 E2B scored 60%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.

Operational comparison

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

Metric	Gemma 4 E2B	MAI-Thinking-1	Comparison
Input / output priceUSD per 1M tokens	Gemma 4 E2B$0 input / $0 output	MAI-Thinking-1Not available	A complete price comparison is not available.
Generation speedtokens per second	Gemma 4 E2BNot available	MAI-Thinking-1Not available	A complete speed comparison is not available.
First-answer latencyseconds to first token	Gemma 4 E2BNot available	MAI-Thinking-1Not available	A complete latency comparison is not available.
Context windowmaximum listed tokens	Gemma 4 E2B128K	MAI-Thinking-1256K	MAI-Thinking-1 lists the larger context window.

Benchmark Deep Dive

Agentic

2 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
τ²-bench resultsSource	20.8%	—	Not comparable
Terminal-Bench 2.0Source	—	46%	Not comparable

Coding

4 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
AA-SciCodeSource	20.9%	—	Not comparable
SWE-bench VerifiedSource	—	73.5%	Not comparable
SWE-bench ProSource	—	52.8%	Not comparable
Terminal-Bench 2.0Source	—	46.0%	Not comparable

Reasoning

3 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
AA-LCRSource	15.0%	—	Not comparable
CritPtSource	0.0%	—	Not comparable
Graphwalks BFS 128KSource	—	90%	Not comparable

KnowledgeMAI-Thinking-1 wins

10 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
GPQASource	43.4%	84.2%	MAI-Thinking-1 leads
MMLU-ProSource	60%	85%	MAI-Thinking-1 leads
Artificial Analysis Intelligence IndexSource	9.3%	—	Not comparable
AA-GPQA DiamondSource	37.5%	—	Not comparable
AA-HLESource	4.8%	—	Not comparable
AA-Omniscience IndexSource	-24.0%	—	Not comparable
AA-Omniscience AccuracySource	6.7%	—	Not comparable
AA-Omniscience Hallucination RateSource	32.9%	—	Not comparable
GPQA-DSource	—	84.2%	Not comparable
SimpleQASource	—	31%	Not comparable

Math

3 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
AIME 2025Source	—	97%	Not comparable
AIME26Source	—	94.5%	Not comparable
HMMT Feb 2026Source	—	84.9%	Not comparable

Multimodal

1 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
AA-MMMU-ProSource	44.6%	—	Not comparable

Inst. Following

2 benchmarks

Benchmark	Gemma 4 E2B	MAI-Thinking-1	Result
AA-IFBenchSource	35.1%	—	Not comparable
IFBenchSource	—	85%	Not comparable

Frequently Asked Questions (2)

Which is better, Gemma 4 E2B or MAI-Thinking-1?

Gemma 4 E2B and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, Gemma 4 E2B or MAI-Thinking-1?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 56.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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