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pi 0.7 vs Bonsai 1.7B

At a Glance

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pi 0.7Physical Intelligence
Pricing and Limits
Context windowMaximum documented tokensNot reported33K
Model facts checkedAug 29, 2026View model evidence →Sep 18, 2026View model evidence →
Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched evidence.

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

Fieldpi 0.7Bonsai 1.7B
DeveloperPhysical IntelligencePrismML
FamilypiBonsai 1 7b
Modelpi 0.7Bonsai 1.7B
Version0.7Bonsai 1.7B
Lifecycleactiveactive
Released2026-04-162026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Robot stateText
Output modalitiesRobot actionText
Context windowUnknown33K
Total parametersUnknown1.7B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableUnknownNo
Self-hostableUnknownYes
Provider accessUnknownUnknown
Capabilitiescross-embodiment, dexterous-manipulation, language-steering, visual-subgoalschat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.25 GB
Weight formatUnknownBinary Q1_0
Robotics model typeVision-language-action modelUnknown
Action representationContinuous robot actions conditioned by multimodal promptsUnknown
Control architectureHigh-level policy, world model, and action expertUnknown
Inference locationUnknownUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsmobile manipulators, bimanual UR5e, multiple fixed manipulatorsUnknown
Training dataRobot demonstrations, autonomous data, egocentric human data, and multimodal web data described by the publisher.Unknown

pi 0.7 Capabilities

cross-embodimentdexterous-manipulationlanguage-steeringvisual-subgoals
Model typeVision-language-action model
InferenceUnknown
Action representationContinuous robot actions conditioned by multimodal prompts
Supported embodiments3
Canonical IDphysical-intelligence/pi-0.7

Bonsai 1.7B Capabilities

chatgeneration
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDprism-ml/Bonsai-1.7B

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Primary Evidence

Sources and Freshness

pi 0.7: a Steerable Model with Emergent CapabilitiesPhysical Intelligence · observed Aug 29, 2026Bonsai 1.7B | PrismML DocsPrismML · observed Sep 18, 2026

Questions

pi 0.7 vs Bonsai 1.7B FAQs

Is pi 0.7 or Bonsai 1.7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both pi 0.7 and Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, pi 0.7 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, pi 0.7 or Bonsai 1.7B?+

Neither model has a larger sourced context window in this comparison. pi 0.7 is — and Bonsai 1.7B is 33K.

Which performs better in benchmarks, pi 0.7 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 pi 0.7 or Bonsai 1.7B be self-hosted?+

Bonsai 1.7B is the only model in this pair currently marked as self-hostable. pi 0.7 is not marked open weight; Bonsai 1.7B is open weight.

Can pi 0.7 and Bonsai 1.7B understand images?+

pi 0.7 is 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, pi 0.7 or Bonsai 1.7B?+

Neither has a larger sourced maximum output. pi 0.7 is — and Bonsai 1.7B is —.

Do pi 0.7 and Bonsai 1.7B support reasoning and tool use?+

pi 0.7: image input. Bonsai 1.7B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, pi 0.7 or Bonsai 1.7B?+

pi 0.7 has 0 sourced provider routes; Bonsai 1.7B has 0, a tie.

Which offers better value, pi 0.7 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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