GoogleGemma 4 E4B
Gemma 4 E4B is a Google open-weights reasoning model, released 3 Apr 2026. Its best configuration (thinking reasoning effort) ranks #535 of 785 on the BenchLeader Index at 44.5 ±4.1, in the lower half. The ± is the point: 295 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 (53) and lowest in multimodal (34). At $0.040 per million tokens blended it is among the cheapest fifth of ranked models. Output speed of 39 tokens per second puts it in the slowest quarter, with a first answer in 51.8 s. 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 3 Apr 2026.stale: no new result in six months
- Blended price
- $0.040/M
- $0.020 in · $0.100 out
- Output speed
- 39 tok/s
- measured by Artificial Analysis
- First answer
- 52 s
- Context
- 131k
- Full answer
- 64 s
- median, reasoning included
- Cost per run
- $0.0082
- one full Intelligence Index run
- Released
- 3 Apr 2026
- Overall index45
- Reasoning42
- Agents & tools41
- Knowledge53
- Instruction following46
- Multimodal34
- Long context40
- Composite39
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.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| no reasoning | 42.5 | #593 | 47 tok/s | 0.83 s | $0.0000 | Agents & tools 40 · Composite 38 · Instruction following 43 · Knowledge 43 · Long context 36 · Multimodal 34 · Reasoning 41 |
| thinkingbest | 44.5 | #535 | 39 tok/s | 52 s | $0.0000 | Agents & tools 41 · Composite 39 · Instruction following 46 · Knowledge 53 · Long context 40 · Multimodal 34 · Reasoning 42 |
| not stated | – | – | – | – | $0.0000 |
How its index has moved
9 Sept 2026 to 21 Oct 2026- 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
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| GPQA Diamond (AA)not in index | 55.0%#406 | 57.6%#391 | Artificial Analysis |
| Humanity's Last Exam (AA)not in index | 4.8%#469 | 3.8%#571 | Artificial Analysis |
| CritPt | 0.3%#271 | 0.6%#254 | Artificial Analysis |
Coding
| Benchmark | thinking | Source |
|---|---|---|
| SciCode (AA)not in index | 24.4%#220 | Artificial Analysis |
| Terminal-Bench 4.0 (AA)not in index | 0.0%#152 | Artificial Analysis |
| Terminal-Bench 2.1 (AA)not in index | 1.9%#221 | Artificial Analysis |
Agents & tools
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| Terminal-Bench Hard | 7.6%#241 | 8.3%#235 | Artificial Analysis |
| τ²-Bench Telecom (AA)not in index | 26.0%#287 | 20.8%#329 | Artificial Analysis |
| GDPval-AA v2.1not in index | – | 0.0%#124 | Artificial Analysis |
| AutomationBenchnot in index | – | 0.5%#208 | Artificial Analysis |
| GDP.pdf (AA)not in index | – | 1.0%#204 | Artificial Analysis |
Knowledge
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA-Omniscience | -41.0#325 | -19.7#243 | Artificial Analysis |
| AA-Omniscience: accuracynot in index | 8.3%#516 | 8.6%#511 | Artificial Analysis |
| AA-Omniscience: non-hallucinationnot in index | 46.2%#138 | 69.1%#49 | Artificial Analysis |
Instruction following
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| IFBench | 40.5%#256 | 44.2%#216 | Artificial Analysis |
Multimodal
| Benchmark | no reasoning | thinking | not stated | Source |
|---|---|---|---|---|
| MMMU-Pro | 51.2%#238 | 51.4%#237 | – | Artificial Analysis |
| MMMU-Pro (official)not in indexeffort not stated | – | – | 52.6%#14 | MMMU |
Long context
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA-LCR | 24.0%#415 | 32.0%#387 | Artificial Analysis |
Composite
| Benchmark | no reasoning | thinking | Source |
|---|---|---|---|
| AA Intelligence Index v4.3.2 | 7.5#474 | 8.9#422 | Artificial 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.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0000 | – | 59.4 s |
| Summarize a 30-page report | 12,000 / 600 | $0.0003 | – | 1.1 min |
| Code edit | 6,000 / 1,500 | $0.0003 | – | 1.5 min |
| Agentic coding session | 60,000 / 4,000 | $0.0016 | – | 2.6 min |
| Structured extraction | 2,000 / 200 | $0.0001 | – | 56.8 s |
More from Google
See also
Questions people ask
- What are Gemma 4 E4B's benchmark scores?
- As of 24 Oct 2026, Gemma 4 E4B (thinking effort) scores 44.5 ±4.1 on the BenchLeader Index, strongest in knowledge (53) and weakest in multimodal (34). That rests on 7 independent benchmark results, and every score on this page links to its publisher.
- How does Gemma 4 E4B rank?
- Gemma 4 E4B (thinking effort) is #535 of 785 ranked configurations on 24 Oct 2026. 295 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 E4B cost per 1M tokens?
- As of 24 Oct 2026, Gemma 4 E4B costs $0.020 per 1M input tokens and $0.100 per 1M output tokens, $0.040 blended (three input tokens per output token).
- When was Gemma 4 E4B released?
- Google released Gemma 4 E4B on 3 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 E4B: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/gemma-4-e4b.