Gemini 3.1 Pro vs Gemma 4 12B

Model Markets Rankings

Intelligence, Cost, and Efficiency

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RankingGemini 3.1 ProGemma 4 12B
CostLower is better · Published-token output estimate#22 of 36$0.161 per LiveBench caseUnrankedNot 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

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
Google DeepMind · previewGemini 3.1 ProVerified Aug 29, 2026
Google DeepMind · activeGemma 4 12BVerified Sep 3, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldGemini 3.1 ProGemma 4 12B
DeveloperGoogle DeepMindGoogle DeepMind
FamilyGemini 3Gemma 4
ModelGemini 3.1 ProGemma 4 12B
VersionGemini 3.1 ProGemma 4 12B
Lifecyclepreviewactive
ReleasedUnknown2026-05-23
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText, Image, Video, Audio
Output modalitiesTextText
Context window1,049K262K
Total parametersUnknown12B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Together Ai (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning, structured_outputs, tools

13 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

Gemini 3.1 Pro Capabilities

chatgenerationreasoningtools
Input price$2.00
Output price$12.00
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.1-pro-preview

Gemma 4 12B Capabilities

chatgenerationreasoningstructured outputstools
Input price
Output price
Serving providers1
Canonical IDgoogle/gemma-4-12B-it

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

Gemini 3.1 Pro vs Gemma 4 12B FAQs

Is Gemini 3.1 Pro or Gemma 4 12B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and Gemma 4 12B, 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 12B?+

Only Gemini 3.1 Pro has a directly sourced input price: $2.00 per million tokens. Only Gemini 3.1 Pro has a directly sourced output price: $12.00 per million tokens.

Which has a larger context window, Gemini 3.1 Pro or Gemma 4 12B?+

Gemini 3.1 Pro has the larger sourced context window. Gemini 3.1 Pro supports 1,049K and Gemma 4 12B supports 262K.

Which performs better in benchmarks, Gemini 3.1 Pro or Gemma 4 12B?+

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 12B be self-hosted?+

Gemma 4 12B is the only model in this pair currently marked as self-hostable. Gemini 3.1 Pro is not marked open weight; Gemma 4 12B is open weight.

Can Gemini 3.1 Pro and Gemma 4 12B understand images?+

Gemini 3.1 Pro is documented with image input; Gemma 4 12B 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 12B?+

Neither has a larger sourced maximum output. Gemini 3.1 Pro is 66K and Gemma 4 12B is —.

Do Gemini 3.1 Pro and Gemma 4 12B support reasoning and tool use?+

Gemini 3.1 Pro: reasoning, tool calling, and image input. Gemma 4 12B: 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 12B?+

Gemini 3.1 Pro has 2 sourced provider routes; Gemma 4 12B has 1, so Gemini 3.1 Pro has broader tracked availability.

Which offers better value, Gemini 3.1 Pro or Gemma 4 12B?+

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.

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