Ministral 3 14B Base 2512 vs pi 0.7

At a Glance

Compare
pi 0.7Physical Intelligence
Pricing and Limits
Context windowMaximum documented tokens262KNot reported
Model facts checkedAug 28, 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

FieldMinistral-3-14B-Base-2512pi 0.7
DeveloperMistral AIPhysical Intelligence
FamilyMinistral 3 14b Base 2512pi
ModelMinistral-3-14B-Base-2512pi 0.7
VersionMinistral-3-14B-Base-25120.7
Lifecycleactiveactive
ReleasedUnknown2026-04-16
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Robot state
Output modalitiesTextRobot action
Context window262KUnknown
Total parameters13.9BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableUnknownUnknown
Self-hostableYesUnknown
Provider accessUnknownUnknown
Capabilitiesgenerationcross-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.

Ministral 3 14B Base 2512 Capabilities

generation
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDmistralai/Ministral-3-14B-Base-2512

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

Primary Evidence

Sources and Freshness

Questions

Ministral 3 14B Base 2512 vs pi 0.7 FAQs

Is Ministral 3 14B Base 2512 or pi 0.7 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Ministral 3 14B Base 2512 and pi 0.7, 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 pi 0.7?+

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 pi 0.7?+

Neither model has a larger sourced context window in this comparison. Ministral 3 14B Base 2512 is 262K and pi 0.7 is —.

Which performs better in benchmarks, Ministral 3 14B Base 2512 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 Ministral 3 14B Base 2512 or pi 0.7 be self-hosted?+

Ministral 3 14B Base 2512 is the only model in this pair currently marked as self-hostable. Ministral 3 14B Base 2512 is open weight; pi 0.7 is not marked open weight.

Can Ministral 3 14B Base 2512 and pi 0.7 understand images?+

Ministral 3 14B Base 2512 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, Ministral 3 14B Base 2512 or pi 0.7?+

Neither has a larger sourced maximum output. Ministral 3 14B Base 2512 is — and pi 0.7 is —.

Do Ministral 3 14B Base 2512 and pi 0.7 support reasoning and tool use?+

Ministral 3 14B Base 2512: image input. pi 0.7: image input. Feature support does not establish relative quality.

Which is available from more inference providers, Ministral 3 14B Base 2512 or pi 0.7?+

Ministral 3 14B Base 2512 has 0 sourced provider routes; pi 0.7 has 0, a tie.

Which offers better value, Ministral 3 14B Base 2512 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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