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Gemini 3.1 Pro vs pi 0.7

At a Glance

Compare
Gemini 3.1 ProGoogle DeepMind
pi 0.7Physical Intelligence
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#9 of 4679.7 score · 3/3 sources · completeUnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#27 of 44$0.161 per LiveBench caseUnrankedNot in the 44-model eligible cohort
EfficiencyHigher is better · MM Efficiency v1.5#9 of 3859.2 score · 3/3 sources · completeUnrankedNot in the 38-model eligible cohort
Pricing and Limits
Context windowMaximum documented tokens1,049KNot reported
Model facts checkedAug 29, 2026View model evidence →Aug 29, 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

FieldGemini 3.1 Propi 0.7
DeveloperGoogle DeepMindPhysical Intelligence
FamilyGemini 3pi
ModelGemini 3.1 Propi 0.7
VersionGemini 3.1 Pro0.7
Lifecyclepreviewactive
ReleasedUnknown2026-04-16
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText, Image, Robot state
Output modalitiesTextRobot action
Context window1,049KUnknown
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesUnknown
Self-hostableNoUnknown
Provider accessGoogle AI (Standard), Google Gemini (Standard)Unknown
Capabilitieschat, generation, reasoning, toolscross-embodiment, dexterous-manipulation, language-steering, visual-subgoals
Robotics model typeUnknownVision-language-action model
Action representationUnknownContinuous robot actions conditioned by multimodal prompts
Control architectureUnknownHigh-level policy, world model, and action expert
Inference locationUnknownUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsUnknownmobile manipulators, bimanual UR5e, multiple fixed manipulators
Training dataUnknownRobot demonstrations, autonomous data, egocentric human data, and multimodal web data described by the publisher.

Gemini 3.1 Pro Capabilities

chatgenerationreasoningtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDgoogle-deepmind/gemini-3.1-pro-preview

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

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Primary Evidence

Sources and Freshness

Gemini 3.1 Pro Preview | Gemini APIGoogle DeepMind · observed Aug 29, 2026pi 0.7: a Steerable Model with Emergent CapabilitiesPhysical Intelligence · observed Aug 29, 2026

Questions

Gemini 3.1 Pro vs pi 0.7 FAQs

Is Gemini 3.1 Pro or pi 0.7 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.1 Pro and pi 0.7, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini 3.1 Pro or pi 0.7?+

Only Gemini 3.1 Pro has a directly sourced input price: $2.00 per million tokens. Only Gemini 3.1 Pro has a directly sourced output price: $12.00 per million tokens.

Which has a larger context window, Gemini 3.1 Pro or pi 0.7?+

Neither model has a larger sourced context window in this comparison. Gemini 3.1 Pro is 1,049K and pi 0.7 is —.

Which performs better in benchmarks, Gemini 3.1 Pro or pi 0.7?+

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

Can Gemini 3.1 Pro or pi 0.7 be self-hosted?+

Neither model is the only model in this pair currently marked as self-hostable. Gemini 3.1 Pro is not marked open weight; pi 0.7 is not marked open weight.

Can Gemini 3.1 Pro and pi 0.7 understand images?+

Gemini 3.1 Pro is documented with image input; pi 0.7 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini 3.1 Pro or pi 0.7?+

Neither has a larger sourced maximum output. Gemini 3.1 Pro is 66K and pi 0.7 is —.

Do Gemini 3.1 Pro and pi 0.7 support reasoning and tool use?+

Gemini 3.1 Pro: reasoning, tool calling, and image input. pi 0.7: image input. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini 3.1 Pro or pi 0.7?+

Gemini 3.1 Pro has 2 sourced provider routes; pi 0.7 has 0, so Gemini 3.1 Pro has broader tracked availability.

Which offers better value, Gemini 3.1 Pro or pi 0.7?+

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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