BenchLeader

Gemma 4 E2B

Reasoning effort

Gemma 4 E2B is a Google open-weights reasoning model, released 2 Apr 2026. Its best configuration (thinking reasoning effort) ranks #624 of 785 on the BenchLeader Index at 41.6 ±5.2, in the lower half. The ± is the point: 308 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in knowledge (51) and lowest in multimodal (27). At $0.050 per million tokens blended it is among the cheapest fifth of ranked models. It has been measured at 3 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 2 Apr 2026.stale: no new result in six months

Blended price
$0.050/M
$0.040 in · $0.080 out
Output speed
–
First answer
–
Context
131k
Full answer
–
Cost per run
–
Released
2 Apr 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index42
  2. Reasoning41
  3. Agents & tools36
  4. Knowledge51
  5. Instruction following41
  6. Multimodal27
  7. Long context32
  8. Composite38

Reasoning-effort configurations

The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.

EffortIndexRankSpeedFirst answerChat reply costCategories
no reasoning39.1#696––$0.0000Agents & tools 36 · Composite 37 · Instruction following 37 · Knowledge 34 · Long context 32 · Multimodal 24 · Reasoning 41
thinkingbest41.6#624––$0.0000Agents & tools 36 · Composite 38 · Instruction following 41 · Knowledge 51 · Long context 32 · Multimodal 27 · Reasoning 41
not stated––––$0.0000

How its index has moved

9 Sept 2026 to 21 Oct 2026
344147
  • thinking
  • no reasoning

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Reasoning

Benchmarkno reasoningthinkingSource
GPQA Diamond (AA)not in index40.5%#47743.3%#458Artificial Analysis
Humanity's Last Exam (AA)not in index4.7%#4774.8%#475Artificial Analysis
CritPt0.0%#3150.0%#315Artificial Analysis

Coding

BenchmarkthinkingSource
Terminal-Bench 2.1 (AA)not in index0.4%#228Artificial Analysis

Agents & tools

Benchmarkno reasoningthinkingSource
Terminal-Bench Hard2.3%#3203.0%#314Artificial Analysis
τ²-Bench Telecom (AA)not in index22.2%#31420.8%#329Artificial Analysis
GDPval-AA v2.1not in index–0.0%#124Artificial Analysis

Knowledge

Benchmarkno reasoningthinkingSource
AA-Omniscience-60.2#467-23.6#258Artificial Analysis
AA-Omniscience: accuracynot in index8.2%#5186.6%#533Artificial Analysis
AA-Omniscience: non-hallucinationnot in index25.6%#24067.6%#53Artificial Analysis

Instruction following

Benchmarkno reasoningthinkingSource
IFBench33.6%#32538.0%#286Artificial Analysis

Multimodal

Benchmarkno reasoningthinkingnot statedSource
MMMU-Pro41.8%#26344.6%#255–Artificial Analysis
MMMU-Pro (official)not in indexeffort not stated––44.2%#21MMMU

Long context

Benchmarkno reasoningthinkingSource
AA-LCR16.3%#44916.3%#449Artificial Analysis

Composite

Benchmarkno reasoningthinkingSource
AA Intelligence Index v4.3.26.5#5257.8#458Artificial Analysis

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0000––
Summarize a 30-page report12,000 / 600$0.0005––
Code edit6,000 / 1,500$0.0004––
Agentic coding session60,000 / 4,000$0.0027––
Structured extraction2,000 / 200$0.0001––

More from Google

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See also

Questions people ask

What are Gemma 4 E2B's benchmark scores?
As of 24 Oct 2026, Gemma 4 E2B (thinking effort) scores 41.6 ±5.2 on the BenchLeader Index, strongest in knowledge (51) and weakest in multimodal (27). That rests on 7 independent benchmark results, and every score on this page links to its publisher.
How does Gemma 4 E2B rank?
Gemma 4 E2B (thinking effort) is #624 of 785 ranked configurations on 24 Oct 2026. 308 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
How much does Gemma 4 E2B cost per 1M tokens?
As of 24 Oct 2026, Gemma 4 E2B costs $0.040 per 1M input tokens and $0.080 per 1M output tokens, $0.050 blended (three input tokens per output token).
When was Gemma 4 E2B released?
Google released Gemma 4 E2B on 2 Apr 2026. BenchLeader has results for it at 3 reasoning-effort settings.

Data as of 24 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Gemma 4 E2B: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/gemma-4-e2b.