Ministral 3 14B Base 2512 vs Bonsai 4B

At a Glance

Compare
Bonsai 4BPrismML
Pricing and Limits
Context windowMaximum documented tokens262K33K
Model facts checkedAug 28, 2026View model evidence →Sep 18, 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

FieldMinistral-3-14B-Base-2512Bonsai 4B
DeveloperMistral AIPrismML
FamilyMinistral 3 14b Base 2512Bonsai 4b
ModelMinistral-3-14B-Base-2512Bonsai 4B
VersionMinistral-3-14B-Base-2512Bonsai 4B
Lifecycleactiveactive
ReleasedUnknown2026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window262K33K
Total parameters13.9B4B
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableUnknownNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitiesgenerationchat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.57 GB
Weight formatUnknownBinary Q1_0

Ministral 3 14B Base 2512 Capabilities

generation
Serving providers0
Canonical IDmistralai/Ministral-3-14B-Base-2512

Bonsai 4B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Ministral 3 14B Base 2512 vs Bonsai 4B FAQs

Is Ministral 3 14B Base 2512 or Bonsai 4B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Ministral 3 14B Base 2512 and Bonsai 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Ministral 3 14B Base 2512 or Bonsai 4B?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, Ministral 3 14B Base 2512 or Bonsai 4B?+

Ministral 3 14B Base 2512 has the larger sourced context window. Ministral 3 14B Base 2512 supports 262K and Bonsai 4B supports 33K.

Which performs better in benchmarks, Ministral 3 14B Base 2512 or Bonsai 4B?+

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

Can Ministral 3 14B Base 2512 or Bonsai 4B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Ministral 3 14B Base 2512 is open weight; Bonsai 4B is open weight.

Can Ministral 3 14B Base 2512 and Bonsai 4B understand images?+

Ministral 3 14B Base 2512 is documented with image input; Bonsai 4B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Ministral 3 14B Base 2512 or Bonsai 4B?+

Neither has a larger sourced maximum output. Ministral 3 14B Base 2512 is — and Bonsai 4B is —.

Do Ministral 3 14B Base 2512 and Bonsai 4B support reasoning and tool use?+

Ministral 3 14B Base 2512: image input. Bonsai 4B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Ministral 3 14B Base 2512 or Bonsai 4B?+

Ministral 3 14B Base 2512 has 0 sourced provider routes; Bonsai 4B has 0, a tie.

Which offers better value, Ministral 3 14B Base 2512 or Bonsai 4B?+

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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