Bonsai 4B vs Jev

At a Glance

Compare
Bonsai 4BPrismML
JevTypeSafe
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.042TypeSafe · Sep 17, 2026
Output priceFrom · USD / 1M tokensNot reported$0.000TypeSafe · Sep 17, 2026
Context windowMaximum documented tokens33K64K
Model facts checkedSep 18, 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

FieldBonsai 4BJev
DeveloperPrismMLTypeSafe
FamilyBonsai 4bJev
ModelBonsai 4BJev
VersionBonsai 4BJev
Lifecycleactiveactive
Released2026-03-292026-09-15
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Model-specific input
Output modalitiesTextModel-specific input
Context window33K64K
Total parameters4BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableNoYes
Self-hostableYesNo
Provider accessUnknownTypeSafe (Standard)
Capabilitieschat, generationcalibrated-confidence, parallel-evaluation, structured_outputs, typed-decisions
Effective bit width1 bit per weightUnknown
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
Weight size0.57 GBUnknown
Weight formatBinary Q1_0Unknown

Bonsai 4B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Bonsai-4B

Jev Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Bonsai 4B vs Jev FAQs

Is Bonsai 4B or Jev better for coding?+

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

Which is cheaper, Bonsai 4B or Jev?+

Only Jev has a directly sourced input price: $0.042 per million tokens. Only Jev has a directly sourced output price: $0.000 per million tokens.

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

Jev has the larger sourced context window. Bonsai 4B supports 33K and Jev supports 64K.

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

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

Can Bonsai 4B or Jev be self-hosted?+

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

Can Bonsai 4B and Jev understand images?+

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

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

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

Do Bonsai 4B and Jev support reasoning and tool use?+

Bonsai 4B: none of these features are definitively sourced. Jev: none of these features are definitively sourced. Feature support does not establish relative quality.

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

Bonsai 4B has 0 sourced provider routes; Jev has 1, so Jev has broader tracked availability.

Which offers better value, Bonsai 4B 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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