Bonsai 1.7B vs Bonsai 4B

At a Glance

Compare
Bonsai 4BPrismML
Pricing and Limits
Context windowMaximum documented tokens33K33K
Model facts checkedSep 18, 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

FieldBonsai 1.7BBonsai 4B
DeveloperPrismMLPrismML
FamilyBonsai 1 7bBonsai 4b
ModelBonsai 1.7BBonsai 4B
VersionBonsai 1.7BBonsai 4B
Lifecycleactiveactive
Released2026-03-292026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window33K33K
Total parameters1.7B4B
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableNoNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitieschat, generationchat, generation
Effective bit width1 bit per weight1 bit per weight
Weight size0.25 GB0.57 GB
Weight formatBinary Q1_0Binary Q1_0

Bonsai 1.7B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Bonsai-1.7B

Bonsai 4B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Bonsai 1.7B vs Bonsai 4B FAQs

Is Bonsai 1.7B or Bonsai 4B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Bonsai 1.7B and Bonsai 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Bonsai 1.7B 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, Bonsai 1.7B or Bonsai 4B?+

Neither model has a larger sourced context window in this comparison. Bonsai 1.7B is 33K and Bonsai 4B is 33K.

Which performs better in benchmarks, Bonsai 1.7B or Bonsai 4B?+

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

Can Bonsai 1.7B or Bonsai 4B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Bonsai 1.7B is open weight; Bonsai 4B is open weight.

Can Bonsai 1.7B and Bonsai 4B understand images?+

Bonsai 1.7B is not 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, Bonsai 1.7B or Bonsai 4B?+

Neither has a larger sourced maximum output. Bonsai 1.7B is — and Bonsai 4B is —.

Do Bonsai 1.7B and Bonsai 4B support reasoning and tool use?+

Bonsai 1.7B: none of these features are definitively sourced. Bonsai 4B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Bonsai 1.7B or Bonsai 4B?+

Bonsai 1.7B has 0 sourced provider routes; Bonsai 4B has 0, a tie.

Which offers better value, Bonsai 1.7B 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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