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Model profile

Gemma 4 E4B

GoogleCurrentReleased Apr 2, 2026
Data verified
Overall Score
43.2Public #155 of 200
Arena Elo
Not listed
Eligible category ranks
0of 8
Price (1M tokens)
$0 in / $0 out
API pricing
Speed
Not listed
Context
128K

Evidence coverage

14 of 323 tracked benchmarks are published. 0 are verified and 14 provisional. 6 of 8 categories are measured.

Updated July 23, 2026Methodology
Published / tracked
14 / 323
Verified
0
Provisional
14
Categories with evidence
6 / 8

Evidence by category

  • Agentic1 benchmark
    Reported
  • Coding1 benchmark
    Reported
  • Reasoning2 benchmarks
    Reported
  • Knowledge8 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal1 benchmark
    Reported
  • Inst. Following1 benchmark
    Reported
Open WeightSelf-hostReasoning
Confidence:
Low
e4b

Gemma 4 E4B ranks #155 out of 200 models on the public leaderboard with an overall score of 43.2/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Gemma 4 E4B is a open weight model with a 128K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

Gemma 4 E4B sits inside the Gemma 4 family alongside Gemma 4 31B, Gemma 4 26B A4B, Gemma 4 12B, Gemma 4 E2B. This profile currently has 14 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 42.5843.87

  1. Ling 2.6 Flash
    InclusionAI
    #15443.87
    Ling 2.6 Flash is #154 with a score of 43.87.
    Compare
  2. Gemma 4 E4BCurrent model
    Google
    #15543.2
    Gemma 4 E4B is #155 with a score of 43.2.
  3. Mistral Medium 3
    Mistral
    #15643.2
    Mistral Medium 3 is #156 with a score of 43.2.
    Compare
  4. Sarvam 105B
    Sarvam
    #15742.97
    Sarvam 105B is #157 with a score of 42.97.
    Compare
  5. Claude 4 Sonnet
    Anthropic
    #15842.79
    Claude 4 Sonnet is #158 with a score of 42.79.
    Compare
  6. GPT-OSS 20B
    OpenAI
    #15942.74
    GPT-OSS 20B is #159 with a score of 42.74.
    Compare
  7. DeepSeek R1 Distill Qwen 32B
    DeepSeek
    #16042.58
    DeepSeek R1 Distill Qwen 32B is #160 with a score of 42.58.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

No eligible category percentile is available from the published evidence yet.

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%1 benchmarkReportedScore pending
CodingRank Not rankedWeight 20%1 benchmarkReported52.0
ReasoningRank Not rankedWeight 17%2 benchmarksReported25.4
KnowledgeRank Not rankedWeight 12%8 benchmarksReported67.4
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank Not rankedWeight 12%1 benchmarkReported52.6
Inst. FollowingWeight 5%1 benchmarkReportedScore pending

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic1 benchmark
τ²-bench resultsReported

τ²-Bench Tool-Agent-User Evaluation

20.8%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Coding1 benchmark
AA-SciCodeReported

Artificial Analysis SciCode

24.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning2 benchmarks
AA-LCRReported

Artificial Analysis Long Context Reasoning

30.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

0.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge8 benchmarks
MMLU-ProReported

Massive Multitask Language Understanding Professional

69.4%Weighted 30%
Source: Reported upstream sourceProvenance: Reported row carried from an upstream public source. Displayable on BenchLM, but not treated as verified unless explicitly marked otherwise.
GPQAReported

Graduate-Level Google-Proof Q&A

58.6%Weighted 7%
Source: Reported upstream sourceProvenance: Reported row carried from an upstream public source. Displayable on BenchLM, but not treated as verified unless explicitly marked otherwise.
Artificial Analysis Intelligence IndexReported
12.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

57.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

3.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

-20.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

8.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

31.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Multimodal1 benchmark
AA-MMMU-ProReported

Artificial Analysis MMMU-Pro

51.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Inst. Following1 benchmark
AA-IFBenchReported

Artificial Analysis IFBench

44.2%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does Gemma 4 E4B perform overall in AI benchmarks?

Gemma 4 E4B has 14 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is Gemma 4 E4B good for knowledge and understanding?

Gemma 4 E4B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B good for coding and programming?

Gemma 4 E4B has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B good for reasoning and logic?

Gemma 4 E4B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B good for agentic tool use and computer tasks?

Gemma 4 E4B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B good for multimodal and grounded tasks?

Gemma 4 E4B has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B good for instruction following?

Gemma 4 E4B has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.

Is Gemma 4 E4B open source?

Yes, Gemma 4 E4B is an open weight model created by Google, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Which sibling models are related to Gemma 4 E4B?

Gemma 4 E4B belongs to the Gemma 4 family. Related variants on BenchLM include Gemma 4 31B, Gemma 4 26B A4B, Gemma 4 12B, Gemma 4 E2B.

Does Gemma 4 E4B have full benchmark coverage on BenchLM?

Not yet. Gemma 4 E4B currently has 14 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Gemma 4 E4B?

Gemma 4 E4B has a published context window of 128K, which determines how much text it can process in a single interaction.

Last updated: July 23, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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