Gemini 3.1 Pro vs Gemma 4 E4B
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Gemini 3.1 Pro | Gemma 4 E4B |
|---|---|---|
| CostLower is better · Published-token output estimate | #22 of 36$0.161 per LiveBench case | UnrankedNot in the 36-model eligible cohort |
Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Gemini 3.1 Pro | Gemma 4 E4B |
|---|---|---|
| Developer | Google DeepMind | Google DeepMind |
| Family | Gemini 3 | Gemma 4 |
| Model | Gemini 3.1 Pro | Gemma 4 E4B |
| Version | Gemini 3.1 Pro | Gemma 4 E4B |
| Lifecycle | preview | active |
| Released | Unknown | 2026-03-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image, Video, Audio |
| Output modalities | Text | Text |
| Context window | 1,049K | 131K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Deepinfra (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
13 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Gemini 3.1 Pro Capabilities
Gemma 4 E4B Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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Gemini 3.1 ProGoogle DeepMind | vs | GLM-5.3Z.ai | cross-developer peerstext |
Gemini 3.1 ProGoogle DeepMind | vs | Hy4 previewTencent | cross-developer peerstext |
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Gemini 3.1 ProGoogle DeepMind | vs | Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3.1 Pro vs Gemma 4 E4B FAQs
Is Gemini 3.1 Pro or Gemma 4 E4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and Gemma 4 E4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3.1 Pro or Gemma 4 E4B?+
Gemini 3.1 Pro is $2.00 and Gemma 4 E4B is $0.020 per million tokens, so Gemma 4 E4B is cheaper on this metric. Gemini 3.1 Pro is $12.00 and Gemma 4 E4B is $0.10 per million tokens, so Gemma 4 E4B is cheaper on this metric.
Which has a larger context window, Gemini 3.1 Pro or Gemma 4 E4B?+
Gemini 3.1 Pro has the larger sourced context window. Gemini 3.1 Pro supports 1,049K and Gemma 4 E4B supports 131K.
Which performs better in benchmarks, Gemini 3.1 Pro or Gemma 4 E4B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 3.1 Pro or Gemma 4 E4B be self-hosted?+
Gemma 4 E4B is the only model in this pair currently marked as self-hostable. Gemini 3.1 Pro is not marked open weight; Gemma 4 E4B is open weight.
Can Gemini 3.1 Pro and Gemma 4 E4B understand images?+
Gemini 3.1 Pro is documented with image input; Gemma 4 E4B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3.1 Pro or Gemma 4 E4B?+
Neither has a larger sourced maximum output. Gemini 3.1 Pro is 66K and Gemma 4 E4B is —.
Do Gemini 3.1 Pro and Gemma 4 E4B support reasoning and tool use?+
Gemini 3.1 Pro: reasoning, tool calling, and image input. Gemma 4 E4B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3.1 Pro or Gemma 4 E4B?+
Gemini 3.1 Pro has 2 sourced provider routes; Gemma 4 E4B has 2, a tie.
Which offers better value, Gemini 3.1 Pro or Gemma 4 E4B?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.