Olmo 3.1 32B Instruct vs Bonsai 1.7B

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens66K33K
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

FieldOlmo-3.1-32B-InstructBonsai 1.7B
DeveloperAi2PrismML
FamilyOlmo 3 1 32b InstructBonsai 1 7b
ModelOlmo-3.1-32B-InstructBonsai 1.7B
VersionOlmo-3.1-32B-InstructBonsai 1.7B
Lifecycleactiveactive
ReleasedUnknown2026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window66K33K
Total parameters32.2B1.7B
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableUnknownNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitieschat, generation, toolschat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.25 GB
Weight formatUnknownBinary Q1_0

Olmo 3.1 32B Instruct Capabilities

chatgenerationtools
Serving providers0
Canonical IDallenai/Olmo-3.1-32B-Instruct

Bonsai 1.7B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Olmo 3.1 32B Instruct vs Bonsai 1.7B FAQs

Is Olmo 3.1 32B Instruct or Bonsai 1.7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3.1 32B Instruct and Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

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, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

Olmo 3.1 32B Instruct has the larger sourced context window. Olmo 3.1 32B Instruct supports 66K and Bonsai 1.7B supports 33K.

Which performs better in benchmarks, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

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

Can Olmo 3.1 32B Instruct or Bonsai 1.7B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Olmo 3.1 32B Instruct is open weight; Bonsai 1.7B is open weight.

Can Olmo 3.1 32B Instruct and Bonsai 1.7B understand images?+

Olmo 3.1 32B Instruct is not documented with image input; Bonsai 1.7B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

Neither has a larger sourced maximum output. Olmo 3.1 32B Instruct is 33K and Bonsai 1.7B is —.

Do Olmo 3.1 32B Instruct and Bonsai 1.7B support reasoning and tool use?+

Olmo 3.1 32B Instruct: tool calling. Bonsai 1.7B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

Olmo 3.1 32B Instruct has 0 sourced provider routes; Bonsai 1.7B has 0, a tie.

Which offers better value, Olmo 3.1 32B Instruct or Bonsai 1.7B?+

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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