Gemma 4 31B vs Jev

At a Glance

Compare
Gemma 4 31BGoogle DeepMind
JevTypeSafe
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.090Openrouter · Sep 22, 2026$0.042TypeSafe · Sep 17, 2026
Output priceFrom · USD / 1M tokens$0.34Openrouter · Sep 22, 2026$0.000TypeSafe · Sep 17, 2026
Context windowMaximum documented tokens262K64K
Model facts checkedSep 3, 2026View model evidence →Sep 17, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldGemma 4 31BJev
DeveloperGoogle DeepMindTypeSafe
FamilyGemma 4Jev
ModelGemma 4 31BJev
VersionGemma 4 31BJev
Lifecycleactiveactive
Released2026-03-112026-09-15
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Model-specific input
Output modalitiesTextModel-specific input
Context window262K64K
Total parameters31BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessCerebras (Standard), Deepinfra (Standard), Google Gemini (Standard), Openrouter (Standard), Together Ai (Standard)TypeSafe (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolscalibrated-confidence, parallel-evaluation, structured_outputs, typed-decisions
Maximum Choice cardinalityUnknown255 options
Default request rate limitUnknown1200 requests per minute
State plus longest question limitUnknown32000 tokens
Combined state and questions limitUnknown64000 tokens
Default token rate limitUnknown250000 tokens per second

Gemma 4 31B Capabilities

chatgenerationreasoningstructured outputstools
Serving providers5
Canonical IDgoogle/gemma-4-31B-it

Jev Capabilities

calibrated-confidenceparallel-evaluationstructured outputstyped-decisions
Serving providers1
Canonical IDtypesafe/jev

Primary Evidence

Sources and Freshness

Questions

Gemma 4 31B vs Jev FAQs

Is Gemma 4 31B or Jev better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemma 4 31B and Jev, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemma 4 31B or Jev?+

Gemma 4 31B is $0.090 and Jev is $0.042 per million tokens, so Jev is cheaper on this metric. Gemma 4 31B is $0.34 and Jev is $0.000 per million tokens, so Jev is cheaper on this metric.

Which has a larger context window, Gemma 4 31B or Jev?+

Gemma 4 31B has the larger sourced context window. Gemma 4 31B supports 262K and Jev supports 64K.

Which performs better in benchmarks, Gemma 4 31B or Jev?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Gemma 4 31B or Jev be self-hosted?+

Gemma 4 31B is the only model in this pair currently marked as self-hostable. Gemma 4 31B is open weight; Jev is not marked open weight.

Can Gemma 4 31B and Jev understand images?+

Gemma 4 31B is documented with image input; Jev is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemma 4 31B or Jev?+

Neither has a larger sourced maximum output. Gemma 4 31B is — and Jev is —.

Do Gemma 4 31B and Jev support reasoning and tool use?+

Gemma 4 31B: reasoning, tool calling, and image input. Jev: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Gemma 4 31B or Jev?+

Gemma 4 31B has 5 sourced provider routes; Jev has 1, so Gemma 4 31B has broader tracked availability.

Which offers better value, Gemma 4 31B or Jev?+

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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